Data Scientist, Entry Level

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The Voleon Group is a technology company focused on applying advanced AI and machine learning techniques to investment management. As a Data Scientist, you will be responsible for deriving insights from complex datasets, ensuring data integrity, and communicating findings to both research staff and executive leadership.

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

Qualification:

Required:

• 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 demonstrating excellence in communication
• Bachelor’s degree in a quantitative discipline (statistics, biostatistics, data science, computer science, or a related field)

Preferred:

• 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