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Major · Multi-Interdisciplinary

Bridging finance fundamentals with modern data-science tooling

Financial Analytics (CIP 30.7104) sits at the intersection of finance and data science, training you to model financial big data with machine learning, statistical inference, and cloud-based platforms. About 557 students complete it across 12 institutions — small numbers, since most universities still file these students under broader Finance or Analytics labels.

Schools offering
12
Annual completions
557
Typical degree level
Associate's + Bachelor's
Median earnings (5yr)

About this major

Financial Analytics (CIP 30.7104) is a multi-interdisciplinary major that fuses finance domain knowledge with modern data-science methods. The CIP definition centers on financial big data modeling — algorithms, cloud-based financial technologies, machine learning applied to markets, statistical inference, dynamic modeling, knowledge management, and decision communication. In practice, that translates into a curriculum that pairs corporate finance, investments, derivatives, and risk with SQL, Python (pandas, NumPy, scikit-learn), R, Bloomberg or FactSet, Excel and VBA, and visualization tools like Tableau or Power BI. Cloud-data exposure through Snowflake, Databricks, or AWS shows up in the better programs.

The major fits students drawn to financial markets who also want to write code, not just read it. It rewards comfort with statistical reasoning, willingness to debug a Python notebook the night before a deliverable, and the patience to translate ambiguous portfolio or risk questions into testable models. Students who pair the academic work with internships in equity research, FP&A, fintech, or risk management ladder fastest.

One grounded observation about scale: only 557 students complete this CIP across 12 institutions nationally — a small footprint that reflects administrative grouping more than student demand. Most universities still file equivalent students under Finance, General (CIP 52.0801, 42,214 completions) or Business Analytics (CIP 30.7102, 1,032). Bachelor’s-relevant career destinations from the named SOC list run from financial and investment analysts ($101,350 median, +5.7% growth) through management analysts ($101,190, +8.8%) and on to data scientists ($112,590, +33.5% projected growth) — high-wage outcomes when paired with the right credential stack.

Section 3 · Careers

Where this major leads

Occupations most often associated with this major, from the federal BLS+O*NET crosswalk. Job-growth projections and median wages are national.

Occupation Median wage Job growth Typical education
Management analysts $101k +8.8% Bachelor's degree
Financial managers $162k +14.8% Bachelor's degree
Financial and investment analysts $101k +5.7% Bachelor's degree
Data scientists $113k +33.5% Bachelor's degree
Business teachers, postsecondary $97k +5.7% Doctoral or professional degree
Section 4 · Earnings

Earnings at a glance

Median graduate earnings from the federal College Scorecard, 5 and 10 years out.

Earnings data is not yet available at this major's level of granularity. See the concentration hub for family-level figures.

Who this major is for

Good signs this major fits: you’re drawn to financial markets and corporate finance and you’re willing to push your coding to working-fluency level rather than coast on Excel; you want a finance career that treats SQL and Python as table stakes rather than nice-to-haves; you’re aiming at corporate FP&A, equity research, risk management, or fintech roles where the modeling and the domain matter equally; you’ve confirmed your target program teaches real Python and statistics, not just dashboarding; and you’re open to starting the CFA Level I track during the bachelor’s as a differentiator against generic Finance graduates.

Reasons to pause: the CIP is small and uneven across schools — only 12 institutions report graduates and program quality varies sharply, so audit the curriculum for actual coding depth before committing. If your goal is high-frequency trading, prop trading, or quant research at firms like Citadel Securities, Two Sigma, or Jane Street, this major alone will not get you there — those firms recruit CS, math, physics, and statistics undergrads, and the typical path runs through an MS in Mathematical Finance or Financial Engineering at programs like CMU MSCF, NYU, Princeton, Columbia, or Cornell. If you want broader finance recognition with recruiters, Finance, General (CIP 52.0801, 42,214 completions) is the dominant signal. If you want pure technical depth without the finance domain, Data Science, General (30.7001) or Financial Mathematics (27.0305, 611 completions) point that direction. And the financial-manager wage of $161,700 is a mid-career outcome after years of experience — never an entry-level expectation.

Section 6 · Where to study

Top colleges for Financial Analytics

Ranked by annual completions at the associate's or bachelor's level — a proxy for program scale.

College Location Assoc. Bach. Total
University of Pennsylvania Philadelphia, PA 0 332 332
Brigham Young University-Idaho Rexburg, ID 0 139 139
Lamar University Beaumont, TX 0 62 62
New Jersey Institute of Technology Newark, NJ 0 19 19
Middle Georgia State University Macon, GA 3 0 3
Georgia Highlands College Rome, GA 1 0 1
University of Illinois Urbana-Champaign Champaign, IL 0 1 1
Lebanon Valley College Annville, PA 0 0 0
Worcester Polytechnic Institute Worcester, MA 0 0 0
Atlanta Metropolitan State College Atlanta, GA 0 0 0

Considering this direction?

We've taken a hard look at the debt, earnings trajectory, and degree-level tradeoffs for the Financial Analytics field. Read our verdict before you commit.

Is Financial Analytics worth it? Read verdict
Section 9 · Frequently asked

Common questions

What do Financial Analytics majors actually study day-to-day?
Coursework pairs the finance side (corporate finance, investments, derivatives, financial markets, risk) with the data-science side (statistical inference, machine learning, dynamic modeling, data visualization, project management). The CIP 30.7104 definition explicitly names financial big data modeling, algorithms, cloud-based fintech, knowledge management, and effective decision communication. Toolset reality: SQL plus Python (pandas, NumPy, scikit-learn), R, Excel and VBA (still very much used in finance), Bloomberg or FactSet terminals, Tableau or Power BI, and exposure to cloud-data stacks like Snowflake or Databricks. Most programs end with a capstone tied to real market or portfolio data.
How does this differ from a regular Finance major or a Data Science major?
Finance, General (CIP 52.0801, 42,214 completions) is the dominant traditional path — heavier on accounting, valuation, and markets, lighter on programming. Data Science, General (CIP 30.7001) leans the other way — heavier math and code, lighter on finance domain. Financial Analytics (30.7104, 557 completions) sits between them, and the differentiator is real domain depth in finance plus working fluency with the modern analytics stack. If you want generalist finance, 52.0801 will be more recognized by recruiters; if you want pure quant tooling, 30.7001 or Financial Mathematics (CIP 27.0305, 611 completions) signal stronger.
What jobs are realistic from this major?
The named SOC list anchors on financial and investment analysts ($101,350 median, +5.7% growth) and management analysts ($101,190, +8.8%) at the bachelor’s-typical-entry tier, with data scientists ($112,590, +33.5% projected growth) and financial managers ($161,700, +14.8%) as longer-horizon destinations. Realistic first jobs include corporate FP&A analyst, equity research associate, risk analyst at a bank, fintech data analyst, and credit or portfolio analyst roles. Financial-manager wages reflect mid-career outcomes after years of finance experience, not entry-level pay.
Is this the right major if I want to work in quantitative trading or hedge funds?
Be honest with yourself here. Top quant-research and prop-trading employers (Citadel Securities, Two Sigma, Jane Street, DRW, Renaissance) recruit primarily from CS, math, physics, and statistics undergrads, not from this CIP. The 30.7104 label by itself does not open that door. The competitive pre-quant track usually means doubling down on math and CS, then targeting an MS in Mathematical Finance or Financial Engineering — programs like CMU MSCF, NYU Mathematical Finance, Princeton MFin, Columbia MAFN, or Cornell Financial Engineering. This major is durable for buy-side equity research, corporate finance, risk management, and fintech roles — but not the high-frequency trading pipeline.
What credentials should I stack alongside the degree?
The CFA (Chartered Financial Analyst, three levels) is the gold standard for buy-side equity research and asset management — Level I is takeable as an undergrad. The FRM (Financial Risk Manager) is the equivalent signal for bank and hedge-fund risk roles. CAIA (Chartered Alternative Investment Analyst) targets hedge fund, private equity, and real estate roles. Bloomberg Market Concepts (BMC) is a quick early-career signal of terminal fluency. None of these are required to land a first job, but starting the CFA Level I track during the bachelor’s is a meaningful differentiator versus generic Finance graduates.
Where does this major actually exist as a bachelor’s program?
The producer list is concentrated. University of Pennsylvania leads with 332 bachelor’s completions, followed by Brigham Young University–Idaho (139), Lamar University (62), New Jersey Institute of Technology (19), and a long tail of programs with handful-level enrollment including Worcester Polytechnic Institute, Stevens-style technical schools, and a few state universities. The 557-total nationally is small because most universities still file equivalent students under broader Finance (52.0801) or Business Analytics (30.7102) labels. If your target school doesn’t offer 30.7104 specifically, a Finance major plus an analytics or data-science minor or a quantitative-finance concentration produces a substantively similar transcript.