Schools with Financial Analytics Degrees

In the world of finance, money does the talking, but data does the walking. Companies can’t survive without financial analytics professionals who know how to identify risks, evaluate financial performance, and increase profits. Sound like your jam? Use our real-world guide to learn more about education pathways, career opportunities, and salary numbers for finance data analysts. Ready to make a decision? Jump ahead to our comprehensive listings of financial analytics degrees & certificates in the USA.

What is Financial Analytics?

What Do Financial Analytics Professionals Do?

In a nutshell, they use advanced data analysis and statistical & computational techniques to make effective financial decisions. This is a job that goes far beyond playing around with Excel! Financial analytics professionals deploy their skills in R & Python, statistical modeling, data mining, econometrics, Machine Learning (ML) and AI to tackle complex challenges. Pursue this career and you may be asked to:

• Analyze Large Financial Datasets: Extract, clean, and process huge volumes of financial data from a variety of sources to identify trends, patterns, and anomalies.
• Conduct Risk Assessments: Evaluate financial risks by analyzing historical data; use quantitative methods to assess potential impacts on business decisions.
• Monitor Investments & Portfolios: Deploy analytics to create accurate & timely reports on the performance of investments and portfolios.
• Create Financial Models: Build and maintain financial models—including valuation models, budget forecasts, and scenario analyses—to support strategic planning and investment decisions; develop predictive models to forecast financial metrics such as revenue, risk, and market trends.
• Automate Financial Processes: Design & implement automated solutions for data reporting, financial analysis, and risk management; create FinTech products that drive efficiency gains.
• Collaborate with Teams: Work cross functionally with finance, IT, operations, sales, and other business units to improve profits and ensure that data strategies are aligned with organizational goals.
• Create User-Friendly Reports: Transform complex financial data into clear, concise reports & data visualizations so that management can make informed decisions.

Why Choose Financial Analytics?

Financial analytics professionals get to stretch their muscles in programming and problem-solving to answer all kinds of questions. Many of these questions will be directly related to everyday concerns (e.g. budget forecasts). But a number of them will involve working with other teams on strategic and operational challenges—how can we use data to save more money? How can we make more money?

For example, in addition to the standard arsenal of analytics methods, financial analytics experts are also interested in industry-specific applications like:

• Cash-Flow Analysis: Evaluating cash inflows and outflows to manage liquidity and predict future cash needs.
• Investment Portfolio Optimization: Using analytics to allocate assets in a portfolio in order to maximize returns.
• Product Profitability Analysis: Assessing the profitability of individual products to optimize pricing & resource allocation.
• Scenario Analysis: Modeling different financial scenarios to assess potential impacts on business outcomes.
• Customer Lifetime Value Analysis: Estimating the total value a customer brings to the business over time.
• Cost Optimization: Analyzing spending patterns to identify areas for cost reduction & efficiency improvement.
• Sales Forecasting: Predicting future sales based on historical data and market trends.
• Capital Budgeting: Evaluating investment opportunities to determine their potential return.

A couple of things to keep in mind:

• Financial analytics is a niche field, so some employers are playing catch up to its possibilities. You may need to help them understand why your work & technical skills are different to that of a financial analyst with a degree in finance.
• You should be in love with finance & financial markets before you commit yourself. In fields like investment banking, work can involve long hours and an unrelenting focus on profit. Look up the descriptions for job titles. Chat to industry experts and current students. Make an informed decision.

What Does a Degree in Financial Analytics Look Like?

Financial Analytics Degree Pathways

Run your eye down the degrees in our listings and you’ll notice that universities have yet to settle on a standard major for financial analytics students. That means you’ll need to be careful when you’re making a choice! The thrust of the major can dictate what kinds of jobs you’ll be ready for after graduation.

• Financial Analytics: You’ll be focusing on financial analytics topics from the get go. Universities will usually launch you straight into areas like financial strategy, computational finance, financial modeling, and FinTech applications. And all of the courses in programming, data analytics, and AI will have a financial slant. This is a technical degree for technical positions.
• Finance: A finance degree will give you a broader view of the finance sector than a pure analytics major. For example, you may get to investigate ideas around financial management, investment analysis, portfolio management, mergers & acquisitions, and international finance before you dig into a financial analytics concentration. Some may even prepare you for the CFA®.
• Financial Engineering: You’ll get to tackle high-level problems in areas like securities valuation, derivatives, portfolio structuring, and risk management using advanced mathematical models & computational skills. As one financial engineer on Reddit notes: “It’s as much an engineering degree as a finance degree and folks in those programs are (and need to be) hard core math/programming nerds.”
• Business Analytics: You’ll start by learning how analytics & data science can be applied to major business concerns—think of areas like marketing, supply chains, management science, and data mining for business decisions. Once you’re in the concentration, you can delve into topics like financial modeling, derivatives & risk management, investments, etc.
• Data Analytics: Data analytics majors use statistical and quantitative methods, computational tools, and predictive models to solve problems in ANY industry. So the core of the major is going to focus on skills like data warehousing, data visualization, management & information systems, prescriptive analytics, and so on.
• Business Administration: Degrees like the BBA or MBA are concerned with management, strategy & decision-making. You’ll always be taking core courses in areas like operations management, marketing, accounting, ethics & business law. It’s a good degree for leaders & C-level aspirants, but not for folks who are aiming for technical positions.
• Dual Majors: If you’re torn between a business-focused major and a technical degree, why not shoot for both? For example, American University offers a combo MS in Finance: Financial Analytics and an MBA. In a Bentley alumni interview, Amrita Choudhary noted: “The dual degree set me apart from other graduate students as the combination of management and technical skills is what most companies require, specifically for management positions.”

Hallmarks of a Great Financial Analytics Degree

Financial analytics professionals straddle two worlds: finance and data analytics & data science. So it pays to look for programs that will give you real-world exposure to both realms. We particularly favor degrees and certificates that feature:

• CFA® training embedded in the curriculum
• Practical coursework that mimics workplace scenarios
• Preparation for relevant certifications
• Student-run investment funds and portfolios
• Virtual trading floors
• Finance, investment, stock trading & analytics competitions
• Student finance clubs
• Access to financial data tools like Bloomberg, FactSet, Morningstar, Capital IQ, Compustat, etc.
• Networking events in financial districts
• Industry internships available as electives
• Adjunct professors currently working in the field
• Capstone projects created with corporate partners

How to Choose a School of Business

Choose wisely. When you commit to a degree in financial analytics, you’re paying as much for the networking & career connections as the teaching and the coursework! Jobs in finance are often built on relationships.

Start by looking for universities that have gained:

• AACSB accreditation for the School of Business
• CFA® affiliation—here’s how to search for CFA®-affiliated universities
• Recognition as a Bloomberg Experiential Learning Partner (ELP)

Then look at whether the School of Business offers:

• Scholarships to financial analytics students
• Unique financial strengths (e.g. American’s optional Graduate Certificate in Islamic Finance)
• Opportunities to work on projects with research institutes like the NSF-funded Center for Research toward Advancing Financial Technologies (CRAFT)
• Travel funding for analytics competitions & conferences
• Comprehensive career resources, including mock interviews, job fairs & internship opportunities
• Verifiable job placements for recent graduates

Above all, think about the reputation of the School of Business and its geographic connections to the financial industry. Schools like Santa Clara University, Golden Gate, and Stanford will have tight connections to Silicon Valley. NYU, Stevens, and Rutgers are located in (or very near) the financial capital of the USA. American University will have ties to the government & federal contractors. Location matters.

Financial Analytics Coursework & Requirements

Admissions Requirements for Financial Analytics Majors

Use the handy admissions links in our listings to get a sense of whether you qualify for entry. Because financial analytics is such an unusual technical field, it really pays to read the requirements carefully. We saw a huge amount of difference in what universities were expecting from candidates. You may be perfect for one degree and completely wrong for another.

Undergraduate

Universities will be looking for candidates with a high school diploma or GED and good grades in mathematics and any other relevant subjects. You may or may not need to submit your SAT or ACT scores—check admissions links in our listings to see if they’re mandatory.

Once you’ve been accepted into university, be sure to keep your grades up. For example, at Wright State, all students intending to major in business at the Raj Soin College of Business must have a minimum 2.5 GPA on at least 30 semester credit hours of undergraduate coursework.

Graduate

Almost every university in our listings has a different set of requirements for the Master of Science in Financial Analytics (MSFA). Some are happy to consider candidates from a wide range of backgrounds; others will want to see finance geeks. Use the admissions links to get a handle on whether you qualify. Here are a few more things we noticed in our research:

• Bachelor’s Degree: In general, universities will favor candidates with an undergraduate degree in finance, accounting, business, computer science, IT, mathematics, or related fields. However, plenty of schools like Santa Clara University are happy to consider all majors. If you don’t have a background in finance, accounting, and math, you may be required to complete prerequisite courses in those areas.
• GPA: The standard minimum is a 3.0 GPA on undergraduate coursework; top-notch schools will have a higher threshold. You can always ask the program coordinator for the average GPA of successful applicants if you want to get a sense of your chances. Schools like Golden Gate University will also allow candidates with low GPAs to submit a statement of purpose & résumé to prove they are ready for graduate study.
• GMAT/GRE: Check each school! We’ve seen GMAT or GRE scores being mandatory, optional, waived for qualified candidates, or simply ignored. For instance, at the University of South Florida, you ostensibly need a minimum GMAT score of 550 (or the equivalent GRE score). But USF will also consider strong candidates with lower scores. And it will grant test waivers to students with high GPAs or those who have passed Level 1 of the CFA® exam.
• Undergraduate Coursework: For an MFTA, you may be expected to show evidence of credits in university-level math (typically calculus and statistics) or economics & accounting or financial management & investment concepts or even quantitative & technical courses. It’s going to depend on the difficulty of the master’s degree and its focus.
• Work Experience: Most universities will accept applicants who are straight out of undergraduate study, but you’ll have a better shot at being accepted if you’ve walked the walk. For instance, Seton Hall University states that candidates with prior work experience in analytics will prove especially competitive in the admission process. And Santa Clara notes that many MS students have 1-3 years of experience (including internships) prior to enrolling.

Your choice of major is going to affect the admissions requirements. For example:

• MSFE: If you’re applying to a financial engineering graduate program, universities are going to want to see a BS in a field like engineering, mathematics, physics, computer science, or economics. You’ll also need to be ready to show proof of undergraduate coursework in calculus, linear algebra, programming (e.g. Java, C++, R or Python), and probability & statistics. GPA thresholds can be higher than the MSFA—we’ve seen minimums like 3.25.
• MBA: MBA requirements tend to be less stringent than those for technical degrees. You may be expected to have a bachelor’s degree in business to apply. Or you may be simply asked to show that you have an understanding of business concepts, statistics, and analytics techniques.

Sample Coursework for Financial Analytics Majors

Once you’ve decided on your focus, take advantage of the coursework links in our listings to compare curricula side-by-side. This will give you the chance to decide whether the courses are at the right level of difficulty for your background.

Bachelor’s Degree

It’s rare to find a bachelor’s degree that’s 100% devoted to financial analytics. Instead, universities will usually offer it as a concentration within a more recognizable major like business analytics, business administration, data science, finance, and the like. For example:

• Penn State’s World Campus Online Bachelor of Science in Functional Data Analytics: Financial Analytics is super-heavy on standard analytics coursework, supplemented by finance-specific credits in Corporation Finance, Intermediate Financial Modeling, Investment & Portfolio Analysis, and Use Cases in Financial Analytics.
• CCGA’s Bachelor of Science in Data Science: Financial Analytics has scores of credits in analytics & data science, complemented by finance courses in Principles of Accounting, Intermediate Accounting, Financial Statement Analysis, Foundations of FinTech, Financial Technologies, Commercial Banking and FinTech, and Securities Analysis.
• UNH’s Bachelor of Science in Finance & Financial Analytics is much more evenly spread. It contains a solid core of coursework in accounting, business finance & law, marketing, management & organization, as well as credits in the major (e.g. Financial Accounting, Financial Decision Marketing, Credit & Risk Analysis, Financial Analytics & Capstone) and electives.

If you’re looking for a “typical” bachelor’s degree in financial analytics, Worcester Polytechnic Institute’s Bachelor of Science in Financial Technology (FinTech): Financial Analytics has an excellent model. The curriculum blends business & finance credits with a hefty dose of computer science. Here’s what four years of study would cover:

• General Education (GE) Requirements: Humanities & Arts, Microeconomics & Macroeconomics, and Basic Science
• College-Level Math: Calculus, Applied Statistics, and Linear Algebra.
• Business Foundations: Legal Environment of Business Decisions, Financial Statements for Decision Making, Risk Analysis for Decision Making, Organizational Behavior & Change, and Ethics & Social Responsibility.
• Computational & Technical Courses: Computer Science Foundations, Business Applications of Blockchain, and AI with Business Applications.
• Analytics Foundations: Data Analysis for Decision Making, Prescriptive Analysis, and Business Intelligence.
• Financial Analytics Concentration: Choose from electives in Data Science, Computational Data Intelligence, Business Data Management, Database Systems, Data Mining, Stochastic Models, Simulation Modeling & Analysis, and more.
• Capstone: The final Major Qualifying Project (MQP) is a team-based, professional-level design or research experience.

Undergraduate Certificate

Undergraduate certificates in financial analytics are rare, but they do exist—our listings will have all the details. They’re going to feature a few introductory analytics courses mixed in with finance courses. Having said that, each school will prioritize different skill sets. For instance:

• UNF’s Undergraduate Certificate in Financial Analytics is devoted to exploring fixed income theories & strategies and giving students real-world experience in investment research, financial modeling, investing capital, and managing a portfolio.
• SFSU’s Undergraduate Certificate in Financial Analytics is much more concerned with advanced math, programming, and technical credits in financial engineering & financial analytics.

Talk to your professors and mentors about whether you should add a certificate to your current plan of study.

Master’s Degree

It’s worth sitting down with a cup of coffee and spending an hour or so visiting the coursework links in our listings. Some graduate degrees in financial analytics will be aimed at relative beginners who want to get up-to-speed in finance concepts & data analytics fundamentals; others will be much more rigorous & challenging. Your choice of major is also going to be incredibly important.

We went digging into MSFA programs to find out if they shared any common threads. Here are some of the most popular courses:

• Financial Strategy & Decision Making
• Corporate Finance: Theory, Tools & Concepts
• Financial Modeling
• Advanced Financial Management
• Quantitative Analysis
• Investment Analysis & Portfolio Management
• Derivatives & Risk Management
• Financial Statement Analysis
• Fixed Income Analysis
• Financial Forecasting & Analysis
• Applied Security Analysis
• Capstone Project

In addition, many MSFA programs will include credits that cover technical skill sets, including:

• Data Management & SQL
• Math for Business & Analytics with R
• Econometrics with R
• Data Analytics with Python
• Data Engineering
• Data Mining
• Machine Learning in Finance
• Applications in FinTech and AI

Seton Hall University’s Master of Science in Financial Technology and Analytics (MFTA) even includes required courses in Algorithmic Trading & Application of Robotics and Blockchain for Finance & Crypto Assets.

Remember, too, that you’ll have the opportunity to use the concentration and/or electives to pursue specific areas of interest and impress employers. For example, the University of Pittsburgh offers a team-based Consulting Field Project with an end-of-term competition and a Global Research Practicum with a study abroad component as electives within its Master of Science in Finance & Business Analytics.

Wondering what a MSFA capstone project might look like? Check out Santa Clara University’s real-life examples of MSFA practicums. These experiential learning projects were curated in conjunction with industry partners in Silicon Valley:

• Armanino ESG Competitor Modeling
• Cisco RMA Hotspot Identification
• EY Hospital Pricing Comparison
• Pluto7 CPG Supplier Sustainability & Quality

Graduate Certificate

Our listings contain a solid number of graduate certificates in financial analytics that are offered online or on-campus. There’s a lot of emphasis in these programs on practical learning—some will even prepare you for popular finance certifications like the CFA®.

Just be aware of the difference in difficulty levels! Universities with a strong track record in tech fields may offer graduate certificates that are quite advanced & sophisticated. For instance:

• Stanford School of Engineering’s Online Graduate Certificate in Financial Analytics emphasizes work in areas like probabilistic analysis, stochastic modeling, simulation, data science, investment science, and financial risk analytics.
• Stevens Institute of Technology’s Online Graduate Certificate in Financial Analytics is designed for current finance professionals, financial engineers, and quantitative analysts who would like to go beyond traditional banking and capital markets disciplines.
• UCLA’s Online Graduate Certificate in Quantitative Financial Analytics is geared towards professionals who are gunning for roles like quantitative analyst, model validation quantitative analyst, or a team lead in modeling and trading.
  

However, you’re also going to find more basic offerings like Louisiana State University’s Online Graduate Certificate in Financial Analytics, which covers fundamentals in data analysis, financial modeling & risk management, as well as initial technical training in Python, R, and Excel.

In certain cases, you can customize a certificate to suit your employer’s needs. For instance, University of Nebraska-Lincoln’s Online Graduate Certificate in Financial Analytics has two required courses in Quantitative Methods in Finance and Predictive Analytics and two electives in areas like Portfolio Management, Fixed Income Analysis, Risk & Simulation Modeling, Data Mining & Descriptive Analytics, and more.

Can You Earn a Financial Analytics Degree Online?

Yes. However, distance learning options in financial analytics at the undergraduate level will be limited. You’ll have a lot more choice when it comes to master’s degrees and graduate certificates. Our listings are full of 100% online options that employers may be willing to subsidize. Just make sure you know whether they feature an asynchronous “learn on your own time” format or include synchronous “real-time” elements like Zoom meetings and class discussions.

• Undergraduate Advice: If you desperately need an online program, you could consider earning a data science or data analytics degree with a financial concentration—Penn State World Campus’s Online Bachelor of Science in Functional Data Analytics: Financial Analytics takes this approach. But we’d advise you to opt for on-campus. Because job options in niche finance fields can be limited, it’s important to take advantage of university resources like technical labs & facilities, student competitions, research institutes, internships, and the like. You should also be networking with industry partners and visiting speakers at every opportunity. See our section on Hallmarks of a Great Financial Analytics Degree for more info.
• Graduate Advice: You don’t have to sacrifice quality for convenience at the graduate level—our listings feature a number of sturdy academic players and a few big names (e.g. NYU). But you will need to be comfortable with learning & practicing technical skills on your own. Before you apply, ask to “sit in” on a class. Find out what kinds of software the program provides. Talk to recent alumni and quiz them about their job paths after graduation. Learn what career resources are available to distance education students (e.g. interview prep, virtual career fairs, etc.).  Investigate whether networking opportunities & internships are built into the curriculum. You’re going to be competing with a lot of other smart folks for jobs once you graduate.

What Can You Do with a Financial Analytics Degree?

What Does a Job in Financial Analytics Look Like?

It’s going to depend on the employer & industry. Take a look at the discussion threads on Reddit and you’ll see that financial analytics professionals are getting stuck into almost every aspect of the field:

“Finance is a broad domain. You can be on the revenue side and run revenue or profitability analytics. You could also be on the expense side and analyze company spend on a range of different activities. There are niches like treasury, currency exchange management and others. All of these are backwards facing (i.e. using data of what happened in previous months, quarters, years). You could also go into financial planning and use the history to attempt to predict the future. All of these are finance areas within a typical corporate financial structure.

Here’s an example of what an FP&A analyst working at a F500 company might be asked to accomplish:

“My team’s goal is to provide valuable financial analytics at the business unit level for a variety of stakeholders such as VP of Finance for the business unit, BU Presidents, Controllership, and at times the CFO. As for what I do all day — I have monthly responsibilities surrounding the forecasting process in which I analyze variances between actuals, budgets, prior years, etc. for a specific business unit and communicate those to various leadership. On a yearly basis, we have our budget process and our strategic planning process in which we work cross functionally with the operations, sales, and other teams. This is the busiest but most interesting part of the job as there is more financial modeling involved. We also get many ad-hoc requests to provide data or analytics to answer specific questions or just get more insights on a specific area of the business.”

And here’s another real-world account from an analytics expert working on the financial side within a tech company:

“It could be an awful lot of things, but off the top of my head: reporting on revenue growth but removing currency fluctuations (if you sell in multiple currencies); efficiencies in choices and processes around payment methods (PayPal, Amex, payment provider backends); revenue prediction or just tracking by buyer, location, etc.”

That’s the more exciting stuff. But here are the “bread and butter” tasks that an entry-level financial data analyst would be required to do at Centene, a healthcare company:

• Develop integrated revenue/expense analyses, projections, reports, and presentations
• Create and analyze monthly, quarterly, and annual reports and ensure financial information has been recorded accurately
• Identify trends and developments in competitive environments and presents findings to senior management
• Perform financial forecasting and reconciliation of internal accounts
• Use Planview to create any needed ad hoc reports or reports for regularly scheduled meetings
• Assist with ad hoc technical needs for team

You can use our list of popular job titles and AI tools to make up a list of typical job responsibilities for analysts, but we also recommend taking advantage of LinkedIn and conferences to chat to folks in the field. They’ll be able to tell you how much of their work is mundane and how much is investigative!

Industries Hiring Financial Analytics Grads

Traditionally, finance professionals with serious analytics skills have found jobs with banks and investment firms. But you don’t have to stick to those employers in order to build a worthwhile & successful career. Many industries are struggling with the current volume, velocity, and variety of financial data. Here are some of the biggest ones to consider:

• Major Banks & Investment Firms: Deploy your expertise in investment analysis, portfolio management, financial services, risk management, trading algorithms, and financial modeling.
• FinTech: Modify, enhance, or automate financial services for businesses or consumers.
• Tech Companies: Manage financial operations & investments for companies with interests in multiple sectors.
• Global Consulting Firms: Provide data-driven financial insights & strategies to major clients (many of these consulting firms offer internships).
  
• Healthcare Finance: Create financial forecasts, models & reports to improve operational efficiencies and cut costs.
• Retail & E-Commerce: Use financial analytics to optimize pricing, manage inventory costs, and analyze consumer data.
• Insurance: Model risk, price insurance products, and analyze claims data.
• Energy Sector: Model financial risks, analyze commodity prices, and reduce costs for energy production & distribution.
• Real Estate & Property Management: Assess investment risks, manage financial portfolios, and forecast market trends.
• Manufacturing: Optimize supply chains, manage production & distribution costs, and analyze financial performance across global operations.
• Government & Public Sector Organizations: Manage budgets, forecast financial needs, and optimize resource allocation.

If you look at the Bureau of Labor Statistics (BLS) profiles for Financial & Investment Analysts and Financial Risk Specialists, you’ll notice that they’re employed by all kinds of sectors. In fact, you’re most likely to find them in:

• New York City (financial capital of the USA)
• San Francisco (tech & FinTech)
• Boston (finance & healthcare)
• Chicago (financial services & trading firms)
• Los Angeles (tech & entertainment)
• Washington DC (government & consulting)
• Dallas-Forth Worth (energy)
• Philadelphia (finance & venture capital)

5 Key Career Tips from the Pros

1. Do Your Homework Before Choosing a Degree: And know where you’re going to be happiest. For example, there’s a lot of debate on Reddit threads about whether data analytics or financial analytics is a more rewarding career. Some say that data analysts have a better work-life balance, more career growth opportunities into data science, and infinitely more variety in their work. Others point out that financial data analysts often have great job security and salaries: “The best path to get into a management role is staying on the finance side.” It’s going to be hard to switch streams once you’ve earned your degree, so take your time in making a decision.
2. Coursework is Just the Start: To get a well-paid job in financial analytics, you will need to supplement your class learning with industry internships, real-world class projects, a solid capstone, lots of networking, and relevant financial certifications. In technical fields, employers are much more interested in your work experience than the name of your degree.
3. Try to Avoid Going Into Debt: Financial analytics is a niche field, so jobs will be thinner on the ground. Once you graduate, you don’t want to be stuck with a specialist qualification and loans you can’t pay off. Take advantage of scholarships for data science & analytics students. Ask your employer to subsidize or pay for your master’s degree in return for a work commitment. Learn if a school helps students secure jobs before their degree is finished.
4. Keep Your Options Open Early in Your Career: If you’re having trouble finding dedicated analytics jobs, consider applying to financial analyst positions in firms that you respect. You may not get to deploy your programming skills at first, but you will be building credibility. As one Reddit contributor notes: “I started in insurance on a tech team, a few of us started working more in the data that fed everything, then reporting on that data, which expanded to getting access to and demonstrating Tableau skills, SQL, etc. We eventually expanded out of insurance and into annuities, trades, document solutions, etc. In doing this we became our own shared services team where our titles were finally changed to BI analysts along the way.”
5. Be Ready for Change: AI is automating traditional financial tasks left, right & center. Companies can take advantage of an ever-expanding range of data sources to make financial decisions. In a world of rapidly changing markets, everyone is trying to make business processes & decisions faster, smarter, and cheaper. Financial analytics professionals and data scientists need to be ready to jump—and jump quickly—to keep up with technical developments.

Financial Analytics Job Titles & Salary Numbers

Sample Job Titles for Financial Analytics Majors

Unfortunately, there’s no designated job title for professionals with financial analytics & data science expertise. We’ve seen analytics skills listed under job postings for financial analysts, Business Intelligence (BI) analysts, risk analysts, financial data analysts—the list goes on and on. As a savvy pro on Reddit notes: “There’s a billion different ‘analyst’ positions out there, but only a handful that actually do real analytics.”

Financial Analytics Job Titles

To get you started, here are some of the most common financial jobs that include analytics & data science work:

• Financial Analyst
• Financial Data Analyst
• FP&A Analyst
• Financial Consultant
• Risk Analyst
• Financial Risk Analyst
• Investment Risk Analyst
• Equity Risk Analyst
• Data Analyst (Finance)
• Data Management Analyst
• Investment Analyst
• Portfolio Manager
• Business Intelligence Analyst
• Business Intelligence Developer
• Finance Operations Analyst
• Investment Operations Analyst
• Equity Research Analyst
• Quantitative Analyst
• Treasury Analyst

However, you’re going to need to do a little bit of reverse engineering to find a position that will meet your expectations! When you’re inputting job titles into job sites, add technical keywords like Python, SQL, and Tableau/Power BI to your searches. If you have relevant finance certifications like CFA® and FRM®, include them as well. Otherwise you may get stuck with roles that only require skills in Excel.

Financial Engineering Job Titles

Interested in pursuing a financial engineering role with some financial analytics thrown in? Your job options will be more along the lines of:

• Quant Risk Analyst
• Quant Developer
• Derivative Analyst
• Derivative Trader
• Complex Securities Manager
• Credit Algorithmic Quant
• Credit Analyst
• EFX Trader
• Options Surveillance Analyst
• Algorithmic Trading Modeler
• Risk Management Consultant

Salary Numbers for Financial Analytics Professionals

Salary sites like Glassdoor and Payscale will give you ballpark figures for standard job titles (e.g. financial analyst), but you’ll probably need to dig a little deeper to find out how much analytics professionals in the finance industry are earning.

Pay a visit to the wage maps for Financial & Investment Analysts and Financial Risk Specialists from the Bureau of Labor Statistics (BLS). These will give you a sense of which industries and cities are offering the best wages. You can then compare the numbers with state & city wage data for Operations Research Analysts and Data Scientists.

Generally speaking, the best paying industries for financial & investment analysts tend to be:

• Web Search Portals (e.g. LinkedIn, Google, Meta, X/Twitter, etc.)
• Other Investment Pools & Funds (e.g. Blackrock, Vanguard, Sycamore Partners, etc.)
• Securities, Commodity Contracts, and Other Financial Investments and Related Activities (e.g. Goldman Sachs, Charles Schwab Corporation, Blackstone, Morgan Stanley, etc.)

And the best paying metropolitan areas for these professionals are centers of finance, insurance, technology, and energy—think NYC, San Francisco CA, Bridgeport-Stamford-Norwalk CT, San Jose CA, Missoula MT, Corpus Christi TX, and Boston MA.

Unsurprisingly, the top paying industry for financial risk specialists is Monetary Authorities – Central Bank (e.g. Federal Reserve Banks or Branches). And you’ll find the best salaries for these specialists being offered in regional powerhouses like NYC, Philadelphia PA, Chicago IL, Los Angeles CA, and Dallas-Fort Worth TX.

Financial Analytics FAQ

What’s the Difference Between Financial Analysis and Financial Analytics?

Financial Analysis vs. Financial Analytics

Financial Analysis: In the most conventional sense, financial analysis involves evaluating financial statements, ratios, and market conditions to assess a company’s financial health, performance, and potential risks. Financial analysts are often interested in understanding the opportunities and consequences of different courses of financial action.

Financial Analytics: Financial analytics uses sophisticated statistical & computational techniques—such as predictive modeling, programming, and big data analysis—to generate financial insights and forecasts for more strategic decision-making. Financial analytics is often used in the service of financial analysis.

Financial Analyst Careers

You’ll see these differences play out when you start looking at job postings for financial analysts vs. financial analysts with analytics skills. When it comes to financial analysts, many companies will be happy to hire folks who have a finance-related degree, financial reporting & accounting knowledge, and skills in Excel. As one Reddit contributor notes:

“Compared to data analytics it’s a very non-technical role. Most financial analysts are only really good with Excel, maybe a bit of SQL/Power BI. 80% of the job is about knowing the finance subject matter – understanding accounting, being able to construct a three statement model, budgeting, forecasting, building DCFs [Discounted Cash Flows] and CBAs [Cost Benefit Analyses], etc.”

But in other cases, companies will be specifically looking for financial analysts who have a technical degree (e.g. financial analytics, data analytics, etc.) and a lot of coding & programming expertise. If that’s the kind of job you’re after, you’ll need to include technical keywords in your job searches and talk to employers about their expectations.

What’s the Difference Between Financial Engineering and Financial Analytics?

Financial Engineering vs. Financial Analytics

Financial Engineering: Financial engineering is an advanced technical field that combines data engineering (e.g. creating and analyzing mathematical models to understand financial markets, price financial instruments, and manage risks), data science (e.g. utilizing advanced computational techniques and algorithms to implement trading strategies and optimize portfolios), and high-level mathematical thinking (e.g. exploring the theory behind the prices of options or other derivatives).

Financial Analytics: The field of financial analytics is much simpler. Unlike financial engineers, financial analytics professionals don’t spend their time creating algorithms for automated trading or employing mathematical theories to create profitable portfolios. Instead, they’re busy using existing analytics tools & techniques to extract insights from financial data for decision-making and strategic planning.

Financial Engineer Careers

Our listings include a few financial engineering programs with analytics concentrations, but make sure you check the admissions requirements and talk to recent alumni before you commit yourself. The coursework is going to be extremely challenging and very heavy on math & programming! Here’s what the experts on Reddit have to say about their experiences:

“If you know you want to work in quant finance and the course includes enough maths it’s a really good degree. You’ll learn lots of maths (SDEs, PDEs, probability, numerical analysis, mathematical statistics, real and complex analysis, …) and you’ll get a good intuition for financial concepts (risk-neutral pricing, derivatives, incomplete markets, risk management, …). “

“If you are mathematically inclined (MSc-PhD in some areas like stochastic calc/numerical linear algebra), are familiar with C++ and/or Python, and love researching then absolutely, it’s a dream job. But beware the interviews are extremely rigorous and very few positions exist since some FIs don’t even have a quant desk (took me 3 months 8-14 hours/day to prepare for and go through the multi stage interviews).”

What Technical Skill Sets Should I Be Acquiring?

In addition to a thorough knowledge of Microsoft Excel, here are the baseline skills we’d recommend for an analytics-focused role in finance. These are the ones that are most frequently cited in job listings:

• SQL: Essential for querying & managing databases and accessing & manipulating financial data
• Python & R: Used for data manipulation, statistical analysis, and building financial models
• Tableau & Power BI: Data visualization tools that help transform complex financial data into accessible visual reports
• Statistics: Including statistical methods like hypothesis testing, regression analysis, and predictive modeling that can be used to analyze financial trends and make forecasts
• Machine Learning & AI Literacy: To automate and streamline financial processes

Depending on the job, you may see a preference for knowledge of specific tools & software (e.g. familiarity with Bloomberg Terminal) or experience with Enterprise Resource Planning (ERP) systems like SAP, Oracle & Hyperion. We’ve also seen Alteryx specified in certain job descriptions.

When in doubt, look up the profiles of financial data analysts on LinkedIn and see what skills they list on their profiles. Or talk to people who are currently in the industry. You’ll find a lot of discussion about this topic in message threads:

“I work for an asset management firm (HQ in LA). My team is made up of financial analysts and we use SQL and Tableau for financial reporting and analytics of AUM, cash flow, revenue, etc. No Python though since we use Alteryx for data manipulation and transformation.” Reddit

“Python is used in basically every area of the financial industry; financial data science, machine learning, credit ratings, trading, asset management, etc. It’s excellent for large-scale data analysis, automating repetitive tasks, building sophisticated models, and conducting advanced statistical analysis. Python can be used with Power BI.” Reddit

What Financial Analytics Certifications Should I Be Earning? Do I Need the CFA?

Top 5 Certifications

Based on job postings for financial data analytics & financial analysts with SQL and programming skills, these are the top 5 most requested certifications by employers. Keep in mind that some of them may be regarded as “nice-to-have” rather than a necessity:

1. Chartered Financial Analyst (CFA®): One of the most respected certifications in finance (particularly for investment professionals) and often required for roles in financial analysis, portfolio management, and research analysis. This is the one to prioritize.
2. Financial Risk Manager (FRM®): Designed for folks who specialize in risk management within financial institutions (e.g. Risk Analyst, Investment Risk Analyst, Equity Risk Analyst, and Financial Risk Analyst). Taking the CFA® exams will be a big help in prep: “FRM is easier once you’re done with CFA (speaking from experience). 50% of it gets covered in L1-2.”
3. Certified Public Accountant (CPA®): The CPA can be valuable for roles that require strong accounting and regulatory knowledge; employers often say that “CPA or CFA certification is a plus” in job descriptions.
4. Certified Treasury Professional (CTP): Valuable for specialist roles involving corporate finance, cash management, and treasury operations, including folks who are managing an organization’s financial activities and liquidity (e.g. Treasury Analyst).
5. Financial Modeling & Valuation Analyst (FMVA®): Useful for folks involved in financial modeling, valuation, and business analysis, especially financial analysts who are working on financial forecasting.

We’ve included links to these qualifications (and others) in our certifications section. But remember that you can always use LinkedIn to find out what certifications folks are listing in their profiles!

CFA® Advice

If you’re just starting out, begin by earning the CFA®. Many financial degrees incorporate CFA® preparation into their coursework. In fact, CFA®-affiliated universities will embed at least 70% of the CFA® Program Candidate Body of Knowledge™ (CBOK) into their curricula. Here’s why it’s worth your while:

• Going through the CFA® process (3 exams) will give you a thorough understanding of financial analysis, show employers that you’re devoted to the field, and put you in line for leadership positions.
• Because of its emphasis on finance, CFA® certification is going to be especially useful if you’re majoring in an area like data analytics or business analytics and have gaps in your industry knowledge.
• Everyone in finance knows what CFA® means. If you’ve earned your analytics degree from a school that doesn’t have a strong reputation in business & computer science, certification can help shine up your résumé.

For more advice from graduate students, check out this CFA® thread on Reddit.

Are Financial Analytics Programs STEM-Designated?

The answer is almost always “yes.” Financial analytics qualifies as a Science, Technology, Engineering & Math (STEM) field.

• STEM designation is important for international students who are on F-1 Visas. Earning a STEM-designated degree means that graduates can apply to extend their 12-month optional practical training (OPT) by an additional 24 months.
• Universities will usually state that their financial analytics program is STEM-designated on the degree website. If you’re in any doubt, talk to the program coordinator.

Financial Analytics Resources & Organizations

Career & Job Sites

• Association for Financial Professionals (AFP) Career Center
• eFinancial Careers
• iHireFinance
• OpenQuant

Certifications

• Certified Financial Planner (CFP®)
• Certified Public Accountant (CPA®)
• Certified Treasury Professional (CTP)
• Chartered Alternative Investment Analyst (CAIA)
• Chartered Financial Analyst (CFA®)
• Chartered Financial Consultant (ChFC®)
• Financial Modeling & Valuation Analyst (FMVA®)
• Financial Risk Manager (FRM®)
• View Our List of Analytics Certifications

Competitions & Hackathons

• CFA Institute Research Challenge
• Conference of State Bank Supervisors (CSBS) Data Analytics Competition
• International Quant Championship

Conferences & Networking Events

• ACM International Conference on AI in Finance (ICAIF)
• AI for Finance Summit
• Data Science in Finance Conference
• IEEE Symposium on Computational Intelligence for Financial Engineering and Economics (IEEE CiFer)
• Quantitative Finance Conference
• View Our List of Analytics Conferences

Internships

• Accenture Graduate Programme
• Barclays Internships
• BlackRock Internships
• Bloomberg Internships
• Deloitte Internships
• Ernst & Young (EY) Internships & Student Programs
• Goldman Sachs Internships & Programs
• J.P. Morgan Internships & Programs
• Morgan Stanley Internships
• PwC Internships

Journals

• Financial Analysts Journal
• International Review of Financial Analysis
• Journal of Banking & Finance
• Journal of Business & Economic Statistics
• Journal of Computational Finance
• Journal of Finance & Data Science
• Journal of Financial Data Science
• Journal of Financial Econometrics
• Journal of Financial Markets
• Quantitative Finance

Organizations & Associations

• American Finance Association (AFA)
• Association for Financial Professionals (AFP)
• CFA Institute
• INFORMS Finance Section
• Financial Analytics Research Society (FARS)
• Global Association of Risk Professionals (GARP)
• International Association for Quantitative Finance (IAQF)
• Women in Fintech
• View Our List of Analytics Organizations

Scholarships

• Accounting & Financial Women’s Alliance (AFWA) Scholarships
• CFA Institute Scholarships
• CFP® Certification Scholarships
• Government Finance Officers Association (GFOA) Scholarships
• Jane M. Klausman Women in Business Scholarship Program
• J.P. Morgan AI Research Awards
• Morgan Stanley Richard B. Fisher (RBF) Scholarship Program