Career paths
Where business students win in tech & AI.
Pick a role to see what you'd do, the skills that matter, how to break in specifically from Olin, who hires, and where to start.
AI Product Manager
Own what gets built and why — the bridge between engineering, design, data, and the business. The hiring bar has shifted from "can you write a PRD" to "can you work with a system that's right most of the time, not all of the time" — which is exactly the judgment a business background is good at.
Skills that matter
How to break in from Olin
- Learn the vocabulary first — Reforge's Product Foundations course or Lenny Rachitsky's Product Management Fundamentals (on Maven) teach the frameworks every PM interview assumes you already know.
- Ship one real AI-product artifact, even a scrappy LLM-powered side project, and write it up as a case study with real numbers — usage, a test result, anything measurable.
- Build a simple eval set for that project: a rubric that scores the model's output against defined criteria. This is now the single most-recommended way to prove AI-PM judgment without a CS degree, and it's cheap to build.
- Practice product-sense and case interviews on Exponent, then target Big Tech APM/RPM programs (Google, Meta) as the highest-leverage entry point — both are explicitly built for non-CS, diverse-background hires and rotate you straight into AI-adjacent teams.
- Save OpenAI- and Anthropic-style AI labs for your second job, not your first — both are well-documented as favoring experienced PMs with a shipped AI track record over fresh graduates.
Where they hire
Compensation
Entry-level PM total comp at large tech companies (Google, Meta, Microsoft, Amazon) realistically runs $150K–$270K, per Levels.fyi's crowdsourced leveling data. At mid-size companies or startups, expect closer to $100K–$180K, mostly cash plus speculative startup equity. AI-focused PM roles are widely reported to carry a premium over generalist PM roles at the same level, though the exact size varies by source — treat any specific percentage as directional, not exact.
Start prepping
- Lenny's NewsletterPM industry newsletter + Fundamentals course
- ReforgeProduct Foundations course
- ExponentPM interview prep & question bank
- Aakash Gupta's AI PM BlueprintAI-PM-specific roadmap
Tech Strategy & Consulting
Advise companies on technology and AI decisions — strategy, transformation, and getting it implemented. A classic MBA path that's changed more in the last two years than in the prior twenty: AI is now graded directly in the interview, not just the job.
Skills that matter
How to break in from Olin
- Start 9–12 months before you plan to apply — MBB and Big Four deadlines have moved earlier; McKinsey's Business Analyst deadline landed a full season earlier in the 2026 cycle than in past years.
- Build one or two projects that show applied data or AI work — an analytics internship, a class project with real data, or a small AI tool — to stand out from a generalist consulting applicant.
- Do 15–25+ live practice cases with peers, not just solo drills, before first rounds. Every current prep guide converges on peer-practice volume as the single highest-leverage activity.
- Prepare specifically for an AI-in-the-loop interview: McKinsey now pilots final-round cases worked through its internal AI tool, and BCG's own screening round is administered by an AI chatbot. You're graded on challenging and correcting the AI's output, not just accepting it — practice narrating what you'd delegate to it versus insist on checking yourself.
- Target tech-focused practices directly — McKinsey Digital/QuantumBlack, BCG X, Bain Vector, EY-Parthenon — which often run recruiting touchpoints beyond the generalist track.
Where they hire
Compensation
MBB pay is close to standardized: roughly $135K–$145K total comp for an undergrad Business Analyst, and $262K–$285K for an MBA Associate (base has held flat at $190K–$192K for three straight recruiting cycles). Big Four / boutique tech-strategy work runs $85K–$130K at the undergrad level and $210K–$280K at the MBA level — the premium strategy arms (PwC Strategy&, EY-Parthenon) now sit close to MBB pay. Figures are aggregated from case-prep industry salary trackers, not official firm disclosures — treat as directional.
Start prepping
- BCG's official practice casesfree, built for its AI-chatbot interview
- PrepLoungepeer case-practice community
- RocketBlocksmath & exhibit drilling
- CaseCoachstructured ex-MBB video curriculum
Data, Analytics & AI
Turn data into decisions — from dashboards and experiments to models. Runs from business analyst all the way to the technical ML/AI-engineering track, and both ends are real, hireable outcomes from Olin.
Skills that matter
How to break in from Olin
- Get SQL fluent through deliberate practice, not just a course — it's the single most-tested skill, and the real bar is explaining a dataset and a business question, not just syntax.
- Build 2–3 end-to-end portfolio projects: messy data in, a business question, a defensible recommendation out. Most hiring managers now say a portfolio matters more than a certificate.
- Pick a track: the analyst path (Excel, SQL, Power BI, A/B testing, storytelling) or the more technical path (Python, Snowflake/BigQuery, dbt, applied ML/LLM concepts) — both are real, hireable outcomes from Olin's STEM-designated MS in Business Analytics or the MS in AI for Business.
- Get fluent with AI copilots for the routine parts of the job — drafting SQL, first-pass analysis. Roughly 60% of data postings now expect some AI capability, and "LLM experience" is the fastest-growing skill line in job postings.
- Cast a wide net beyond FAANG — the large majority of data/analytics roles are at mid-size enterprises, banks, and companies mid-digital-transformation, not marquee tech names, and entry-level postings at the very largest companies have gotten more competitive as AI tooling consolidates junior work.
Where they hire
Compensation
Typical entry-level (0–3 yr) analyst-track pay runs $65K–$115K total comp; the more technical analytics-engineering/applied-AI track runs $95K–$175K, per Levels.fyi and industry salary guides. A handful of elite-tech employers report entry-level analyst total comp above $150K, but that's a high-variance outlier band that requires a genuine technical interview loop, not the typical offer. Roles that explicitly name GenAI/LLM/MLOps carry a documented 15–25% premium once you have a year or two of experience.
Start prepping
- DataLemurSQL interview prep, real-interview provenance
- StrataScratchlarge SQL/Python question bank
- Maven Analyticsbusiness-first Excel/Power BI/Tableau courses
- Google Data Analytics Certificatestarter curriculum — pair with a portfolio
Growth, BizOps & GTM
Drive adoption and revenue for tech products — growth, operations, marketing, and partnerships. A genuinely new hybrid role ("GTM Engineer") has emerged in the last two years for people who can pair business judgment with light technical/AI fluency.
Skills that matter
How to break in from Olin
- Learn the three growth pillars — experimentation, growth strategy frameworks, and SEO/content basics. Lenny Rachitsky's "Breaking into Growth" is the clearest current map of what to learn first, and links to the specific courses (Reforge's Experimentation and Growth Series).
- Prove BizOps credibility without a BizOps title: pick one real process in a club, internship, or part-time job, audit it with data, propose and lead a small cross-functional fix, and document the measurable result.
- Get comfortable with SQL and a product-analytics tool (Amplitude, Mixpanel, or GA4) — this is the single most-repeated requirement across growth job postings and clears most internship screens on its own.
- Consider a structured rotational program — Uber's APM program and DoorDash's internship (with an unusually high ~70–80% return-offer rate) both give real ops/growth exposure through a legible application process.
- Build a small "GTM Engineer"-style project — an AI-assisted lead-enrichment or outreach-personalization workflow on top of a tool like Clay or HubSpot. This hybrid RevOps-plus-AI role barely existed three years ago and now pays notably above traditional RevOps — a genuinely differentiated portfolio piece for a business student with some technical curiosity.
Where they hire
Compensation
A 0–3 year hire at a well-known scale-up (Uber, DoorDash, Ramp) realistically lands $95K–$180K total comp, per company-reported leveling data — BizOps-titled roles trend toward the higher end, growth-marketing titles toward the lower-middle. At an early-stage (seed/Series A) startup, expect $60K–$95K base cash plus an equity grant in the low tenths of a percent — genuinely high-variance and illiquid, not a number to bank on.
Start prepping
- Lenny's Newslettergrowth archives + "Breaking into Growth"
- ReforgeGrowth Series & Experimentation courses
- RevGeniusfree, active community with job channels
- Demand Curvegrowth marketing playbooks & newsletter
Tech Investing & VC
Evaluate and back technology and AI companies — venture, growth equity, or corporate development. Genuinely competitive and low-headcount, but there's a real, current on-ramp for students willing to publish their thinking before they have a title.
Skills that matter
How to break in from Olin
- Publish public investment memos or a market map on a specific thesis you can credibly own — this is now literally how VCs evaluate candidates, and it's a portfolio you can start building before you have any job title.
- Apply broadly to student-focused scout/fellowship programs — Contrary Capital's Venture Partner Program and Research Fellowship, Dorm Room Fund, and General Catalyst's Rough Draft Ventures all run live cohorts. Acceptance rates are brutal, so apply to more than one.
- Get real operating experience at a startup first — having actually built something is repeatedly cited as more valuable than a pure finance resume, since junior VC work is fundamentally about judging founders and markets.
- Be honest about headcount: most funds hire single digits of junior people a year, mostly through warm referrals. Growth-equity firms (Insight Partners, General Atlantic, TA Associates) and corporate venture arms (GV, Salesforce Ventures, Microsoft's M12) run more structured, higher-headcount recruiting and are a realistic entry point into tech investing broadly.
- If you're early and want a structured on-ramp, Venture University and GoingVC both run part-time training cohorts built specifically for people without an existing VC network.
Where they hire
Compensation
VC pays less than private equity at every level below partner: a VC analyst realistically earns $85K–$180K total cash comp, an associate $130K–$320K (median ~$210K) — figures from self-reported platforms and industry compensation surveys, not official firm disclosures. Growth-equity associates run notably higher, often $250K–$400K all-in in year one. Carry (a share of fund profits) is the long-term upside, but it's illiquid, vests over 5+ years, and rarely reaches anyone below Principal/VP — model your first few years as base-plus-bonus only, not carry.
Start prepping
- Contrary Research Fellowshippaid, structured public-memo program
- Dorm Room Fundstudent-run pre-seed fund
- StrictlyVCdaily VC/funding newsletter
- The Generalistlong-form investor & company deep dives
Founder / Startup
Start something of your own — or join an early team and help build it from zero to one. WashU Olin was ranked #1 in Poets&Quants' 2026 World's Best MBA Programs for Entrepreneurship — the on-campus resources for this path are genuinely strong, not an afterthought.
Skills that matter
How to break in from Olin
- Talk to 15–20 people in a specific niche using the "Mom Test" method — ask about specific past behavior, not hypothetical opinions — before writing a line of code.
- Use WashU's own pipeline as a forcing function: pitch into the Skandalaris Center's IdeaBounce for early feedback, then The League of Extraordinary Entrepreneurs (Olin's MGT 4775/5775, with a $30,000/semester funding pool and weekly mentorship from alumni founders), then the Skandalaris Venture Competition.
- Ship a scrappy MVP in days using AI app builders (Lovable, Replit Agent, or Bolt.new) so you have something real to put in front of those same 15–20 people, not a semester-long build. The club's project pods are also a low-risk place to practice this exact loop before going out on your own.
- If AI is core to your idea, apply to Mayfield AI Garage @ WashU — a real Silicon Valley VC running a funded program on WashU's own campus, with NVIDIA compute credits included.
- Layer in non-dilutive money before giving up equity: Arch Grants offers $75K–$100K with no equity taken in exchange for headquartering in St. Louis for a year, and T-REX gives free/cheap coworking plus warm intros to local investors.
Where they hire
Compensation
Founder pay is real but modest: pre-seed founders typically pay themselves $50K–$75K (often $0 before funding), rising to roughly $120K–$175K+ post-Series A, per startup-compensation data. The honest tradeoff: tech startups fail at a real, high rate (~63% within five years, mostly from "no market need" or running out of cash) — the equity you're trading cash for is a genuinely skewed bet, not a guaranteed multiplier on salary.
Start prepping
- Y Combinator Startup Schoolfree, self-paced
- "The Mom Test" by Rob Fitzpatrickthe standard customer-discovery text
- The League of Extraordinary EntrepreneursWashU's funded accelerator course
- Skandalaris LaunchpadWashU's funded summer accelerator