The Voleon Group is growing its Feature Engineering team — a small, high-impact group responsible for turning the world's messy, complex datasets into predictive signals that power our machine learning models. As a Data Scientist on this team, you'll dig into raw data from diverse domains and, in collaboration with Research, assist in design and implementation of features that capture what is actually happening in the world. This is data storytelling at its most consequential: every feature you build has a direct path to our investment process.
We're looking for deeply curious people who get genuine satisfaction from wrestling with an unfamiliar dataset, understanding its structure and quirks, and emerging with something that encodes real information. You'll own the full arc from data sourcing and curation through feature construction, statistical validation, and integration into our production systems. We also expect you to actively experiment with AI-powered tools — LLM-based coding assistants, agentic workflows, and whatever comes next — to accelerate your day-to-day work and push the boundaries of what a small team can accomplish.
Responsibilities
- Explore, profile, and curate complex and often messy datasets from third-party vendors and internal sources, developing a deep understanding of what each dataset can and cannot tell us
- Harness financial intuition, academic research, and statistical rigor to inform design and implementation of predictive features in collaborative setting
- Validate features through a disciplined, test-driven framework — including cross-sectional analysis, stationarity testing, and point-in-time correctness — to ensure signals are real and not artifacts of data issues
- Build and maintain data pipelines that bring features from prototype to production, with monitoring for data health and correctness along the way
- Communicate your findings clearly — both the signal you've found and the story of how the data produces it — to researchers and leadership
- Proactively investigate anomalies in data feeds and production behavior, performing root-cause analysis and surfacing issues to relevant stakeholders
- Leverage AI tools to accelerate exploration, coding, and analysis — and share what you learn about effective workflows with the team
Requirements
- 2 years of applied industry experience (including internships) working end-to-end with complex datasets: curation, querying, aggregation, exploratory analysis, and visualization
- Experience using statistical methods to analyze data, identify patterns, conduct root-cause analysis, and translate findings into actionable insights
- Ability to frame and answer questions mathematically
- Ability to infer useful forward-looking directions from the results of retrospective analysis
- Fluency in managing, processing, and visualizing tabular data using SQL and Python (Pandas or Polars)
- Basic software development skills and experience with bash, Linux/Unix, and git
- Ability to refine ambiguous requests into well-scoped analyses and communicate results with clarity and precision
- Bachelor's degree in a quantitative discipline (statistics, data science, computer science, economics, physics, or a related field)
Preferred
- Master's degree in a quantitative discipline
- Prior industry experience or demonstrated interest in finance — academic projects, coursework in financial engineering, or industry internships
- Familiarity with financial datasets such as Compustat, IBES, or similar vendor data
- Experience developing in a production-facing environment with standard tooling (CI/CD, git, workflow orchestration)
- Hands-on experience with AI coding assistants or LLM-based tools in a data science or engineering workflow
- A track record of curiosity-driven exploration — side projects, Kaggle competitions, research papers, or anything that shows you can't leave an interesting dataset alone
Top Skills
What We Do
Founded in 2007 by two machine learning scientists, The Voleon Group is a quantitative hedge fund headquartered in Berkeley, CA. We are committed to solving large-scale financial prediction problems with statistical machine learning. The Voleon Group combines an academic research culture with an emphasis on scalable architectures to deliver technology at the forefront of investment management. Many of our employees hold doctorates in statistics, computer science, and mathematics, among other quantitative disciplines. Voleon's CEO holds a Ph.D. in Computer Science from Stanford and previously founded and led a successful technology startup. Our Chief Investment Officer and Head of Research is Statistics faculty at UC Berkeley, where he earned his Ph.D. Voleon prides itself on cultivating an office environment that fosters creativity, collaboration, and open thinking. We are committed to excellence in all aspects of our research and operations, while maintaining a culture of intellectual curiosity and flexibility. The Voleon Group is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.
