The Voleon Group

Software Engineer, Strategy Research Analytics

The Voleon Group$130K — $155K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Computer Science or relevant field
  • 3+ years in analytics or data infrastructure systems
  • Proficient in Python and SQL
  • Experience with distributed query engines and large-scale compute systems
  • Proven ownership of critical data infrastructure
  • Strong understanding of data modeling and schema design
  • Expertise in metadata management and data governance principles.

Responsibilities

  • Own and operate recurring analytics pipelines with a focus on monitoring and reliability
  • Lead the architectural evolution of the analytics platform and consolidate workflows
  • Align technical approaches across teams to standardize analytics outputs
  • Build and maintain base analytics tables with consistent schema practices
  • Define reliability standards and implement observability for analytics workflows
  • Enhance user experience through thorough documentation and data contracts
  • Optimize SQL query performance and design partitioning for columnar storage
  • Mentor engineers through design reviews and uphold operational standards.

Benefits

  • Collaborative work environment fostering creative thinking
  • Opportunity for strong technical ownership
  • Impact on research velocity and insight generation
  • Work alongside experienced engineers from top tech companies
  • Engagement in meaningful projects improving analytics consistency.
Full Job Description
As a Software Engineer in Strategy Research Analytics, you will lead the design, evolution, and long-term architecture of Voleon's analytics infrastructure supporting research reporting and analysis across strategies. You will own critical recurring analytics pipelines and foundational datasets, while guiding the transition from fragmented, bespoke workflows toward a standardized, observable, and query-native analytics platform. In addition to hands-on implementation, you will shape technical direction, establish reliability standards, and drive consolidation efforts that improve consistency, scalability, and reproducibility across research analytics systems.

You'll collaborate closely with Data Scientists, Researchers, and Data Infrastructure teams to ensure analytics systems run reliably and produce consistent, queryable datasets. This role offers strong technical ownership within a mission-critical area of the research organization, with meaningful impact on research velocity and insight generation.

Your Team

The Research Analytics team sits within Research Engineering and works closely with Data Scientists and Researchers across all of Voleon's core strategies. We look for brilliant people with a passion for solving problems through innovation and engineering fundamentals. You'll work in a collaborative environment that encourages creative thinking and efficient implementation. You'll work alongside experienced engineers recruited from leading technology companies and selected from the sharpest minds at university programs.

The team's mission is to:
  • Stabilize existing analytics pipelines to ensure critical data is available for our data scientist and research partners
  • Implement monitoring/alerting and operational runbooks; participate in incident response and postmortems
  • Standardize outputs from strategy workflows into a unified analytics schema (tables, metrics definitions, partitioning strategy)
  • Improve dataset discoverability via documentation, schema contracts, and metadata/lineage primitives
  • Optimize query performance and cost for distributed engines (Presto/Spark) and columnar formats (Parquet/ORC)


Responsibilities
  • Own implementation and on-going operation of recurring analytics pipelines (e.g., Airflow DAGs) including monitoring, alerting, and reliability improvements
  • Lead architectural evolution of the analytics platform, including schema standardization, DAG consolidation, and modernization of legacy workflows
  • Drive cross-team technical alignment when consolidating duplicated or inconsistent analytics outputs
  • Build and maintain base analytics tables and metrics with strong schema discipline and reproducible computation
  • Define and implement reliability standards (SLOs, observability patterns, runbooks) adopted across analytics pipelines
  • Improve transparency and usability through documentation, discoverability, and clear data contracts
  • Optimize distributed compute and SQL query performance; design data layouts (partitioning, file sizing) for columnar storage
  • Mentor engineers through design reviews and raise the bar for operational and modeling rigor


Requirements
  • Bachelor's degree in Computer Science or equivalent professional experience
  • 3+ years of experience building and operating analytics or data infrastructure systems
  • Strong proficiency in Python and SQL
  • Deep experience with distributed query engines and large-scale compute systems
  • Demonstrated ownership of large-scale or mission-critical data infrastructure
  • Strong data modeling expertise, including schema design, partitioning strategy, and reproducibility considerations
  • Expertise in metadata management, data lineage, and applying robust data governance principles


Preferred Qualifications
  • Experience leading architectural migrations or major refactors of data platforms
  • Familiarity with AWS cloud technologies and on-prem compute clusters (e.g., Slurm, SSH, Unix)
  • Exposure to quantitative research or machine learning environments.
"Friends of Voleon" Candidate Referral Program

If you have a great candidate in mind for this role and would like to have the potential to earn $15,000 if your referred candidate is successfully hired and employed by The Voleon Group, please use this form to submit your referral. For more details regarding eligibility, terms and conditions please make sure to review the Voleon Referral Bonus Program.

About The Voleon Group

The Voleon Group is a quantitative investment management firm that uses advanced mathematical and statistical techniques to identify and exploit market inefficiencies. The company was founded in 2007 by Michael Kharitonov and Jon McAuliffe and is based in San Francisco, California. Voleon's investment strategies are based on machine learning and artificial intelligence, and the company has a team of over 200 researchers and engineers working to develop and improve its algorithms. Voleon manages several funds, including a long/short equity fund and a futures fund, and has a strong track record of performance. The company is known for its rigorous approach to research and its commitment to transparency and ethical behavior.
Learn more about The Voleon Group
Size
200 employees
Industry
Founded
2007

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