Financial Analytics & Risk
For students who want banking, investment, capital markets, portfolio, risk, actuarial, or finance decision-support roles that require quantitative evidence.
A student-facing exploration and job-search planning guide for Decision Analytics majors. Use this site to learn what DAN graduates commonly do, compare role families, test your interests, and build evidence over time. You do not have to pick one path and be done; the pathways below are highlighted because they reflect common DAN outcomes and useful starting points for career conversations.
Do not treat the site as a one-time reading assignment. Work through it in a sequence: learn where students land, compare paths, identify employers and job titles, build evidence, and convert what you learn into a focused search plan.
Start with Employment by Function and outcome trends. Ask: Which functions appear most often? Which pathways match my quantitative and business interests? Which options create questions I should bring to my coach?
Move from broad interest to specific employers and job-title families. Use the site to build a starter list, then validate current openings in 12Twenty, Handshake, LinkedIn, Wake Network, and employer career sites.
Identify the skills your target roles require and connect those skills to class projects, experiential work, certifications, student leadership, internships, and independent practice.
Use your target role, employer list, priority skills, and evidence to create a job-search plan and story you can use in applications, outreach, interviews, and coaching conversations.
| Rank | Function | Count | % of total |
|---|---|---|---|
| 1 | Finance | 30 | 29.4% |
| 2 | Consulting | 27 | 26.5% |
| 3 | Analytics / Data Analytics | 16 | 15.7% |
| — | Function not coded in FDS | 11 | 10.8% |
| 4 | Information Technology | 4 | 3.9% |
| 5 | Marketing/Sales | 4 | 3.9% |
| 6 | General Management | 2 | 2.0% |
| 7 | Operations/Production | 2 | 2.0% |
| 8 | Other | 2 | 2.0% |
| 9 | Accounting | 1 | 1.0% |
| 10 | Actuary | 1 | 1.0% |
| 11 | Human Resources | 1 | 1.0% |
| 12 | Product/Project Management | 1 | 1.0% |
For students who want banking, investment, capital markets, portfolio, risk, actuarial, or finance decision-support roles that require quantitative evidence.
For students who like structured problem solving, client work, operational diagnostics, technology transformation, and analytics-enabled recommendations.
For students who want to build models, analyze data, test assumptions, and translate statistical results into business decisions.
For students who want roles where business systems, product operations, technical requirements, and analytics meet.
For students who want to use campaign, customer, market, pricing, or media data to guide growth decisions.
For students who want to apply DAN skills in sports, healthcare, education, government, nonprofit, or public-impact settings.
Use these employers for banking, markets, investment, risk, portfolio, and financial decision-support searches.
Use these employers for advisory, analytics-enabled strategy, technology transformation, and client-facing problem-solving searches.
Use these employers for product analytics, statistical modeling, marketing analytics, healthcare analytics, sports analytics, and public-impact pathways.
Annual totals provide context for how much outcome activity appears in each source-year file.
Finance and Consulting are the largest DAN function categories; analytics labels are consolidated here for readability.
Financial Services and Consulting are the largest industry channels, followed by Accounting and Technology.
Year-by-year counts for the largest DAN accepted function categories. Analytics/Data Analytics and Analytics are shown separately in the raw source file, but the visual summary above consolidates them.
| Accepted function | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | 2025 | Total |
|---|---|---|---|---|---|---|---|---|---|
| Finance | 8 | 4 | 1 | 4 | — | 4 | 4 | 5 | 30 |
| Consulting | 6 | 4 | 5 | 3 | 2 | 5 | 1 | 1 | 27 |
| Analytics / Data Analytics | 4 | — | 5 | — | 1 | 3 | — | 3 | 16 |
| Information Technology | 2 | 1 | — | — | 1 | — | — | — | 4 |
| Marketing/Sales | — | — | 2 | 1 | — | — | 1 | — | 4 |
| General Management | — | — | — | — | — | — | 2 | — | 2 |
| Total outcomes | 20 | 9 | 22 | 13 | 5 | 12 | 11 | 10 | 102 |
Year-by-year counts for the largest DAN accepted industry categories. Use these industries as research starting points, then validate current opportunities in Handshake, 12Twenty, LinkedIn, Wake Network, and employer career sites.
| Accepted industry | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | 2025 | Total |
|---|---|---|---|---|---|---|---|---|---|
| Financial Services | 5 | 2 | 4 | 1 | — | 4 | 6 | 5 | 27 |
| Consulting | 3 | 4 | 7 | — | — | 4 | 2 | 2 | 22 |
| Accounting | 1 | — | 4 | 2 | — | — | — | 1 | 8 |
| Technology | 5 | — | 2 | — | — | — | — | — | 7 |
| Healthcare | 1 | 1 | 1 | — | 1 | — | — | — | 4 |
| Other | — | — | 2 | — | 1 | — | 1 | — | 4 |
| Management Consulting | — | — | — | 2 | 1 | — | — | — | 3 |
| Retail | — | 1 | 1 | — | — | — | 1 | — | 3 |
| Commercial Banking & Credit | — | — | — | 2 | — | — | — | — | 2 |
| Energy/Utilities | 1 | — | — | — | — | — | 1 | — | 2 |
| Location | 2023 | 2024 | 2025 | Total | Share |
|---|---|---|---|---|---|
| New York | 5 | 2 | 7 | 14 | 50.0% |
| North Carolina | 1 | 3 | 0 | 4 | 14.3% |
| Missouri | 1 | 0 | 1 | 2 | 7.1% |
| California | 0 | 1 | 0 | 1 | 3.6% |
| Connecticut | 0 | 1 | 0 | 1 | 3.6% |
| Florida | 0 | 0 | 1 | 1 | 3.6% |
| Illinois | 0 | 1 | 0 | 1 | 3.6% |
| Minnesota | 1 | 0 | 0 | 1 | 3.6% |
| Coded location total | 8 | 8 | 9 | 25 | 89.3% |
Risk advisory, financial-services consulting, technology advisory, analytics, and client-service pathways.
Growth analytics, customer acquisition, digital marketing, business analytics, and media decision roles.
Business technology solutions, risk advisory, analytics-enabled consulting, and transformation roles.
Analytics, advisory, economic consulting, disputes, financial analysis, and data science project work.
Capital markets, sales and trading, finance analytics, structured products, and banking decision-support.
Investment banking, global markets, asset/wealth management, and analytical finance pathways.
Banking, securities, finance analytics, commercial finance, and wealth/markets roles.
Technology consulting, process redesign, analytics-enabled transformation, and business analyst pathways.
Strategy, operations, growth, organization, and analytics-enabled business problem solving.
Corporate banking, finance, operations, markets, and analytical decision-support roles.
Portfolio analytics, investment operations, risk, client analytics, and market-facing analytical roles.
Strategy, financial-services consulting, operations improvement, and analytics-backed recommendations.
Technology advisory, business advisory, risk, audit analytics, and analytics-enabled professional services.
Operations analytics, product operations, supply-chain decision support, and systems-focused analytical roles.
Builds forecasts, variance analyses, models, and financial recommendations for managers, finance teams, and client-facing groups.
Translates business problems into requirements, analyses, dashboards, process maps, and recommendations.
A flexible entry title across finance, consulting, analytics, product, operations, and business strategy.
Uses campaign, customer, channel, pricing, and funnel data to improve marketing and revenue outcomes.
Cleans, analyzes, validates, and visualizes data to answer business questions and support decisions.
Evaluates markets, assets, performance, and risk to support investment decisions and client recommendations.
Supports transaction analysis, financial modeling, due diligence, valuation, and client materials.
Supports market analysis, trading desks, sales coverage, structured products, and client-facing decision support.
Connects programming, systems, data, and business needs to support technical problem solving and analytics delivery.
Uses structured thinking, stakeholder research, analytics, and business judgment to support consulting or advisory teams.
Build a customized DAN search plan by choosing either a career pathway or job title / role group, selecting a related skill, and connecting that skill to actual Decision Analytics curriculum evidence. Then choose the search track you are running: summer internship or full-time job.
Start with a pathway or role group. Then choose a priority skill and turn DAN coursework, quantitative projects, internships, and portfolio evidence into a targeted search plan.
Use Skill Builder to convert a DAN interest area into visible evidence: statistical reasoning, business problem framing, modeling choices, data preparation, dashboards, technical fluency, ethical judgment, and employer-ready stories. Step 3 is always available, but its curriculum text customizes only after the student completes Step 1 and Step 2.
Select a target role family, review the priority skills for that role, then connect each skill to curriculum, WFU resources, and employer-facing proof.
This Step 3 curriculum map provides default DAN curriculum guidance and becomes personalized after Step 1 role-family and Step 2 priority-skill selections. Use it to choose coursework emphasis, electives, projects, internship evidence, and portfolio artifacts that make the selected DAN career direction credible.
Select a role family to see how to position the business core, math/statistics sequence, computer science/economics electives, and Decision Analytics Seminar seminar work.
Select a Step 2 skill to see how that skill should shape your coursework, data projects, internship deliverables, and portfolio proof.
Use the DAN business core to show employers that your analysis is grounded in how organizations operate: accounting, finance, marketing, operations, management information systems, legal environment, organizational behavior, and management simulation.
Use the math/statistics requirements to show rigor: regression and data science, linear algebra, operations research, probability, statistical learning, and electives that deepen technical credibility.
Use Decision Analytics Seminar and electives to translate technical analysis into business recommendations. Strong DAN evidence explains the problem, data, method, assumptions, limits, recommendation, and decision impact.
Goal: move from “I like analytics” to a first role-family hypothesis and evidence plan.
| Course signal | Career translation |
|---|---|
| STA 112 | Regression, data thinking, and early analytics language |
| DAN business core | Business context for analytics questions |
| MTH foundation | Quantitative rigor and problem-solving discipline |
Goal: pair coursework with one employer-ready artifact before internship interviews.
| Artifact | Best-fit search use |
|---|---|
| Model notebook | Data/statistical modeling, finance analytics |
| Dashboard | Marketing, operations, product, business analytics |
| Recommendation memo | Consulting, business analyst, management roles |
Goal: show employers that you can move from analysis to decision.
| Senior-year evidence | Interview translation |
|---|---|
| Decision Analytics Seminar | Business case, method, recommendation, and decision impact |
| STA/MTH elective | Technical depth and modeling judgment |
| Internship/project | Workplace application and measurable contribution |
| Elective direction | Career positioning | Evidence to build |
|---|---|---|
| Computer science | Data, product, technology, software-adjacent analytics | Code notebook, SQL/Python project, technical requirements brief |
| Statistics / mathematics | Statistical modeling, risk, forecasting, decision science | Model validation, assumptions memo, technical summary |
| Business / finance | Finance analytics, consulting, management analytics | Financial model, market memo, strategy recommendation |
| Economics | Market analysis, policy, finance, public-impact analytics | Trend analysis, causal reasoning, industry brief |
Use these platforms to research employers, find postings, build skills, connect with alumni, and prepare for interviews. Start with the resource that matches your current question; you do not need to use everything at once.
Use outcomes and employer history to identify realistic targets and alumni patterns.
Open 12TwentyFind internships, full-time postings, employer events, and campus recruiting timelines.
Open HandshakeUse alumni connections to learn about teams, tools, timelines, and role expectations.
Open Wake NetworkSearch Wake Forest alumni by employer, location, function, and keyword to learn about analytics teams and referral paths.
Open WFU alumni on LinkedInFind WFUSB-connected alumni, recent graduates, and business-school employer pathways for analytics, consulting, finance, and data roles.
Open WFUSB on LinkedInBuild evidence in Excel, SQL, Python, statistics, data visualization, consulting, and storytelling.
Open LinkedIn LearningUse occupational profiles to identify keywords, skills, and role families for search terms.
Open O*NETVerify current role titles, deadlines, locations, and intern/new-grad programs directly with employers.
Start with employer cardsGenerate audience-specific talking points as you explore and refine your direction. Use this to explain how Decision Analytics combines business context, statistics, modeling, technical fluency, and decision judgment.
Use this before analytics interviews, alumni outreach, technical conversations, and employer events. Step 4 changes the wording, depth, and ask based on who you are speaking with.
Build technical and business-translation skills used in finance, consulting, risk, marketing, operations, and data-focused roles.
How these resources fit: Complement and reinforce skills developed through the academic program while building additional capabilities for specific job titles and functional roles.
Choose a target role, identify the most important gap, and complete the course that helps you create credible evidence for that role.
Use these courses to strengthen responsible AI use, judgment, and communication across business functions.
Use AI productively while checking accuracy, protecting data, and preserving your own judgment.
Employers expect you to frame ambiguous problems, test assumptions, and recommend a practical next step.
Strong analysis only creates value when you can explain it clearly to a client, manager, or teammate.
Start with the cluster closest to your target role. Each cluster pairs two relevant courses with a work sample you can create.
SQL and Python help you move from a provided spreadsheet to independently retrieving, cleaning, and analyzing business data.
Connect the quantitative DAN curriculum to the dashboards and decision tools used by business teams.
Analyst roles require more than correct calculations: they require requirements gathering, stakeholder awareness, and a clear recommendation.
The current DAN pathway is strong in analysis, visualization, and business translation. This pairing adds responsible-use controls, model risk awareness, and scenario-based decision support so students can explain not only a forecast, but also its uncertainty and guardrails.
Pair technical depth with the human skills needed to clarify needs, collaborate, earn trust, and move work forward.
Analysts must clarify the decision, stakeholder need, and business value before touching the data.
Entry-level analysts often must earn adoption without owning the decision or the team.
The power-skill collection aligns with the NACE Career Readiness Competencies and the World Economic Forum Future of Jobs 2025 skills outlook.
Use these only after reviewing several postings for your target title and confirming that the skill appears repeatedly.
Complete one technical course and one translation course. Combine them in a single decision-analysis project with code or calculations, a visual, and a recommendation.
LinkedIn Learning periodically updates course titles and URLs. These links were verified against LinkedIn's public course catalog in July 2026. Course access is provided through Wake Forest University.