Data Scientist

About the role

Voleon is a technology company that applies state-of-the-art AI and machine learning techniques to real-world problems in finance. For nearly two decades, we have led our industry and worked at the frontier of applying AI/ML 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 artificial intelligence and machine learning research as well as highly experienced finance and technology professionals. 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.

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.

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 demonstrating excellence in communication

- Bachelor’s degree in a quantitative discipline (statistics, biostatistics, data science, computer science, or a related field)

PREFERRED QUALIFICATIONS

- 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