Data Scientist, Trading Operations
About the position Voleon is a technology company that applies state-of-the-art machine-learning techniques to real-world problems in finance. For over a decade, we have led our industry and worked at the frontier of applying machine learning to investment management. We have become a multibillion-dollar asset manager, and we have ambitious goals for the future. Your colleagues will include internationally recognized experts in machine learning research as well as highly experienced technology and finance professionals. The people who shape our company come from other backgrounds, including concert music performances, humanitarian aid, opera singing, sports writing, and BMX racing. You will be part of a team that loves to succeed together. In addition to our enriching and collegial working environment, we offer highly competitive compensation and benefits packages, technology talks by our experts, a beautiful modern office, daily catered lunches, and more. The Voleon Group has formed a new team to help advance our data-driven investment initiatives. As a Data Scientist, you will be responsible for harvesting insights from a complex array of data. Your role will involve data curation, analysis, interpretation, visualization, and communication of your findings to members of the research staff and executive leadership. This role is a means to make a difference: as a machine learning company, data insights are essential to our business. As a Data Scientist in Trading Operations, you will be embedded in the Quantitative Trading Strategy team. The team focuses on domain-heavy technical work, such as tuning execution algorithms and optimizing portfolio financing. You will build, maintain, and analyze data pipelines to generate insight consumed by the whole team. You will work at the intersection of trading and research on problems requiring market domain expertise and statistical and quantitative rigor.
Responsibilities
- Design and implement systems to ensure data correctness and monitor data health in data stores and live feeds
- Proactively identify abnormal production behavior and communicate them clearly to relevant stakeholders
- Perform extemporaneous analyses on research and production trading systems with leadership
- Harness financial expertise and statistical analysis to gain actionable insights into our production trading and research systems
- Design and implement analysis pipelines that automate those analyses found to be valuable for ongoing monitoring
Requirements
- 1+ years of applied end-to-end industry experience, including internships working with complex datasets, including curation, querying, aggregation, exploratory data analysis, and visualization
- Experience using statistical methods to analyze data, identify patterns, conduct root cause analysis, discover insights, and recommend solutions
- Ability to frame and answer questions mathematically
- Ability to infer useful forward-looking directions from results of retrospective analysis
- Fluency in managing, processing, and visualizing tabular data using a combination of SQL, Pandas, and R
- Basic software development skills and experience with bash, Linux/Unix, and git
- Ability to refine requirements from ambiguous requests to produce reports
- Excellent communication skills
- Bachelor's degree in a quantitative discipline (statistics, biostatistics, data science, computer science, or a related field)
Nice-to-haves
- Master's degree in a quantitative discipline
- Prior industry experience or displayed interest in finance, such as related academic projects, coursework in financial engineering, or industry internships
- Experience developing in a production-facing environment and familiarity with standard concepts and tooling, e.g., CI/CD, git, Airflow
Benefits
- Medical, dental, and vision coverage
- Life and AD&D insurance
- 20 days of paid time off
- 9 sick days
- 401(k) plan with a company match
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