The Voleon Group hires Software Engineer, ML Research Staff and Data Scientist. Candidates report 4 to 5 interview stages depending on the track (7 distinct rounds across all tracks). Below: what each round tests and how to prepare, the path by track, the timeline, pay and a 4-week prep plan, drawn from candidate reports and The Voleon Group's own recruiting pages.
The Voleon Group interview: quick answer
- StagesBy track: Software Engineer: 5 · ML Research Staff: 4 (7 distinct rounds across all tracks)
- Online assessmentCoding OA / take-home (1-1.5 hr) + Data Analyst SQL/pandas
- Final roundReferences + Background Check: 3 references · background check
- Pay (candidate-reported)Software Engineer, New grad: $250k – $400k total comp
- RolesSoftware Engineer, ML Research Staff, Data Scientist
Preparing for The Voleon Group? Work the rounds in order in the free The Voleon Group interview funnel.
The The Voleon Group interview process at a glance
| # | Round | Format and length | Who takes it | Prep |
|---|---|---|---|---|
| 1 | Online Assessment | Coding OA / take-home (1-1.5 hr) + Data Analyst SQL/pandas | Software Engineer | OA guidePractice |
| 2 | Phone / Tech Screen | 45–60 min · HackerRank / phone | Software Engineer | GuidePractice |
| 3 | Onsite / VO | 4 rounds · 1hr + 2.5hr coding + design | Software Engineer | GuidePractice |
| 4 | ML Research Phone | ~60 min · stats + ML | ML Research Staff | GuidePractice |
| 5 | Research VO + Deep-Dive | 2 × 2 hr · stats / ML / coding / research | ML Research Staff | GuidePractice |
| 6 | Culture / Intro Discussion | ~30–45 min · technical manager | All tracks | GuidePractice |
| 7 | References + Background Check | 3 references · background check | All tracks | Practice |
Stages are listed in the order candidates report them. Formats come from candidate reports and change between cycles, offices and teams; the "Who takes it" column shows which track each round belongs to.
How the The Voleon Group process differs by track
The Voleon Group runs separate loops for different roles. Here is the path each track reports, in order:
- Software Engineer (5 stages): Online Assessment → Phone / Tech Screen → Onsite / VO → Culture / Intro Discussion → References + Background Check
- ML Research Staff (4 stages): ML Research Phone → Research VO + Deep-Dive → Culture / Intro Discussion → References + Background Check
Not sure which track fits you? See quant trader vs quant researcher.
Every The Voleon Group round: what it tests and how to prepare
1Online Assessment
Voleon's OA is coding/take-home: a flagship exchange-execution simulation plus classic algorithm problems (largest bounded sub-grid, anagrams, file parsing, increment-stack), and for analyst roles a 4-SQL + 1-pandas data task. QR / ML Research candidates typically skip this and start with the reading list + research phone below. The bar is high and rejections are fast. Take the auto-graded problems below.
How to prepare
- Practical SWE, not LeetCode-flashy - clean file I/O, stacks, sliding windows.
- Pandas/SQL fluency for DS roles - the data task rejects 4/5 even strong candidates.
- Research rounds are stats/ML deep - know OLS, CV bias-variance, KNN, bootstrapping cold.
The Voleon Group online assessment guide →Practice this round →
2Phone / Tech Screen
One hard LeetCode-style problem + an optimization follow-up, read from stdin / written to stdout with real test cases. The single highest-frequency item is the Basic Calculator series (+−, then ×÷, then parentheses, then variable substitution, then resolving a dict of inter-dependent variable expressions via topological sort).
Question types: mostly coding, especially data structures, complexity analysis, greedy and sorting and searching. Latest candidate report for this round: Mar 2023.
How to prepare
- Master the Basic Calculator series end-to-end — the parentheses and variable-dependency (toposort) follow-ups are where people stall.
- Read stdin / write stdout cleanly and run the real test cases — they expect production hygiene.
- Have the optimization ready — they always push on complexity after a working solution.
Full Phone / Tech Screen guide →Practice this round (8 questions) →
3Onsite / VO
Hard SWE loop: Word Search II. Core: 4-part order-matching engine. Whiteboard: sparse matrix (add/multiply) or hashmap internals. System design: huge-map point→country (quadtree), dependency resolution, distributed crawler.
- Expect an order-matching engine design problem.
Question types: mostly coding, machine learning and market microstructure, especially data structures, complexity analysis, arrays and sorting and searching. Latest candidate report for this round: Dec 2025.
How to prepare
- The order-matching engine is the main filter — structure it cleanly (order books as heaps), handle stop-triggers-stop, and refactor as you add parts.
- Word Search II needs a Trie + pruning (prune by letter, delete found words) to avoid TLE on the 8-direction search.
- Design the sparse-matrix class (coordinate/CSR storage, add + multiply) and reason about a quadtree for the map lookup.
Full Onsite / VO guide →Practice this round (20 questions) →
4ML Research Phone
Stats + ML phone after a reading list (~10 intro, 40 tech, 10 Q&A): OLS closed form, when (XᵀX)⁻¹ exists, gradient-descent least squares in basic numpy, R²-combining, Y~X vs X~Y slope puzzles, E[X|X+Y] for joint normals. Doubly-stochastic matrices, small-sample binomial median test, maybe one numpy coding task.
- About an hour with a PhD researcher: linear algebra, OLS, regression slopes and probability puzzles.
- Say your plan before you compute; interviewers rarely redirect you, and they want the right answer, not only a good process.
Question types: mostly regression, probability and linear algebra, especially matrix operations, correlation, convex optimization and eigenvalues. Latest candidate report for this round: Nov 2025.
How to prepare
- Derive OLS and logistic regression from scratch (closed form + gradient descent + optimal learning rate via the Hessian).
- The regression-range puzzles recur: R² combining bounds and the product of Y~X and X~Y slopes (∈ [0,1]).
- E[X | X+Y] for joint normals and doubly-stochastic-matrix facts are high-frequency.
Full ML Research Phone guide →Practice this round (23 questions) →
5Research VO + Deep-Dive
VO Part 2: a coding round (ex-CS-professor interviewer) and a research deep-dive where a senior researcher probes your PhD work. Fit matters a lot.
- Two back-to-back rounds on statistics and machine learning (earlier reports describe two rounds of about two hours each).
Question types: mostly regression, machine learning and coding, especially matrix operations, correlation, eigenvalues and expected value. Latest candidate report for this round: Nov 2025.
How to prepare
- Be hands-on in R/pandas — fit regressions, interpret p-values, and debug a messy data setup live.
- Know regression-tree build complexity, KNN/k-fold bias-variance, and why L1/L2 (not L½) at a derivation level.
- Own your research — the deep-dive is rigorous and fit-weighted; be able to defend every choice.
Full Research VO + Deep-Dive guide →Practice this round (21 questions) →
6Culture / Intro Discussion
A 2025 addition, a culture/intro discussion with a technical manager or hiring manager: opinions on engineering/ML, behavioral (a proud project, a data-driven decision), and weaknesses. It's a non-trivial gate, not a formality. Reported on both the SWE and QR tracks.
How to prepare
- Have crisp, opinionated views on engineering/ML practices you can defend.
- Prepare a proud project + a data-driven decision story (STAR).
- Be genuine about weaknesses — the manager is reading fit and self-awareness.
Full Culture / Intro Discussion guide →Practice this round →
7References + Background Check
Aggressive closing gates: three references (award-heavy probing for research) plus a background check. Candidates who pass the technical loop are frequently rejected here, so it's a real step.
How to prepare
- Line up three strong references early who can speak to depth and rigor.
- Prep references for detailed probing — especially on research awards/claims.
- Keep your record clean and consistent — the background check is thorough.
Practice the The Voleon Group rounds in order
Each round in the The Voleon Group funnel has its own practice set, with worked solutions and progress tracking. A free account saves your progress across rounds.
A 4-week The Voleon Group prep plan
Built from the order of The Voleon Group's rounds on the Software Engineer path and the topics in each round's practice set. Compress it if your first interview is sooner. Other tracks can swap in their own rounds from the table above.
| When | Focus | What to do |
|---|---|---|
| Week 1 | Foundations | Review coding, regression and machine learning, the topics that dominate The Voleon Group's practice sets. Start with Quant coding course and Statistics & regression course. Work the easy and medium questions in the The Voleon Group question set. |
| Week 2 | Early rounds: Online Assessment and Phone / Tech Screen | Practice coding under time pressure, and read the OA guide. Talk every answer through out loud; interviewers score the reasoning. |
| Week 3 | Later rounds: Onsite / VO, Culture / Intro Discussion and References + Background Check | Move to market microstructure, machine learning and linear algebra. Do timed coding sessions in your interview language. Read how quant superdays work. |
| Week 4 | Rehearse the full loop | Run each practice round in order, redo the questions you missed, and prepare two project stories plus a specific answer to "why The Voleon Group?" (see behavioral questions at trading firms). |
The Voleon Group pay
| Role | Level | Total comp | Notes |
|---|---|---|---|
| Software Engineer | New grad | $250k – $400k | Hard production-coding loop; clean, refactored code is explicitly graded. |
| ML Research Staff | PhD | $350k – $600k | PhD research track; statistics + ML derivations throughout. |
Total compensation means base salary plus bonus and any sign-on, as candidates self-report it. Job postings usually show base salary only, so posted figures and outside salary pages often look lower. Rough ranges, NOT offers. Voleon pays at the top of the market for ML research and engineering; small headcount, very selective. Source: Candidate self-reports (levels.fyi, Glassdoor, and candidate forums) — not employer-verified. Last updated May 29, 2026.
The Voleon Group teams and what their interviews test
Software Engineers face a hard coding loop (Calculator → Word Search II → an order-matching engine → sparse matrix + system design). ML Research Staff (PhD) get a reading list, then statistics + ML rounds with hands-on data work and a research deep-dive. Data Scientists do pandas + regression + statistics; Data Analysts do SQL + pandas.
| Tracks | What it does | What its interviews test |
|---|---|---|
| Software Engineer Software Engineer | Research and trading infrastructure; production code. | HR → phone (Basic Calculator + optimization) → culture discussion → onsite → 3 references + background check. |
| ML Research Staff / QR Researcher | Statistical ML signal research. PhD-heavy. | Reading list → phone (stats + ML + light numpy) → VO part 1 (a statistics round + an ML round, hands-on R/pandas) → VO part 2 (a coding round + a research deep-dive). |
| Data Scientist Data Scientist | Client/applied data research. | HR → pandas data exploration + regression + statistics (p-values, bootstrapping) → onsite real-work data problems. |
About The Voleon Group
| Firm type | Machine-learning hedge fund |
|---|---|
| Trading style | ML-first; production-engineering bar · Systematic / statistical ML |
| Founded | 2007 |
| Headquarters | Berkeley, CA |
| Other offices | New York, London |
| AUM | ~$23B (2026) |
| Employees | ~430 |
| Reported performance | +13.6% (2024) |
| Offices | Berkeley headquarters, plus New York and London |
Culture
Academic ML pedigree (founders from Berkeley CS/stats). The interview experience is consistently described as cold and low-interaction, the bar is very high, and three-reference + background checks frequently cull candidates who pass the technical loop. Recruiter-sourced.
What the interviews feel like
Hard, production-quality coding from stdin/stdout (clean, refactored code matters) for engineers; statistics + ML derivations with live data work for research. No games.
Practice for The Voleon Group on QuantVault
Practice
Courses
Further reading
- How quant superdays work
- Behavioral questions at trading firms
- Market-making game interview guide
- The quant interview process, explained
Similar firms to compare
Firms with a similar business and interview style. Many candidates interview at several of them in the same cycle.
Sources and how this guide is built
- Updated October 20, 2026; firm data last reviewed May 29, 2026; pay last updated May 29, 2026.
- Round detail draws on 40 questions candidates report from The Voleon Group interviews (the most recent report across all rounds is from Jun 2026). A separate curated The Voleon Group question set of 49 problems collects the most useful practice for this firm.
- The Voleon Group's own pages: Voleon careers.
- Public candidate reports and outside interview guides are cross-checked against each other. Where they disagree the page says "reports differ"; details from a single source are marked as candidate reports.
- No actual interview questions are reproduced on this page. The questions, with worked solutions, are in the practice rounds.
The Voleon Group interview FAQ
How many rounds are in the The Voleon Group interview?
It depends on the track: Software Engineer: 5; ML Research Staff: 4 stages. Across all tracks candidates report 7 distinct rounds: Online Assessment, Phone / Tech Screen, Onsite / VO, ML Research Phone, Research VO + Deep-Dive, Culture / Intro Discussion, References + Background Check.
What happens in the The Voleon Group final round?
References + Background Check (3 references · background check). Aggressive closing gates: three references (award-heavy probing for research) plus a background check. Candidates who pass the technical loop are frequently rejected here, so it's a real step.
Does the The Voleon Group process differ by role?
Yes. Software Engineer: Online Assessment, Phone / Tech Screen, Onsite / VO, Culture / Intro Discussion, References + Background Check. ML Research Staff: ML Research Phone, Research VO + Deep-Dive, Culture / Intro Discussion, References + Background Check.
How much does The Voleon Group pay?
Candidate-reported total compensation: Software Engineer (New grad) $250k – $400k; ML Research Staff (PhD) $350k – $600k. These are self-reported totals including bonus, not offers; job postings usually list base salary only.
How should I prepare for the The Voleon Group interview?
Prepare round by round over about four weeks: foundations first, then the early rounds (Online Assessment, Phone / Tech Screen, Onsite / VO), then the later rounds, then a full rehearsal. Each round has its own practice set on QuantVault, and the online assessment has a dedicated guide.
What does The Voleon Group do?
The Voleon Group is a machine-learning hedge fund headquartered in Berkeley, CA.
Is there an online assessment for Voleon research roles?
Typically not. Research candidates start with a live technical screen.
Is there a trading game at Voleon?
No. None is reported.
Are references really a gate at Voleon?
Yes. Reference checks come after the interviews and can decide the outcome.
Does Voleon send preparation material?
Yes. Candidates report receiving an interview preparation guide or reading list.
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