Data Research and Acceleration Analyst

Location: New York, New York, United States

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Duties: Analyzing and enriching a wide range of structured and unstructured big data into datasets for analysis. Communicating data-driven analysis and insights in the form of “data studies” that enable a nuanced understanding of our data and inform our investment research process. Amplifying, measuring, and exposing data quality and completeness through automation and a process-driven approach. Operating and extending our data infrastructure platform to deliver production-grade data curation and analysis capabilities. Developing deep domain expertise on our datasets, the underlying behaviors manifested through these datasets, and the associated, measurable economic phenomena. 

Minimum education and experience required: Master’s degree or equivalent in Mathematics, Statistics, Economics, Computer Science, or related field OR Bachelor’s degree or equivalent in Mathematics, Statistics, Economics, Computer Science, or related field plus 2 years of experience in data analysis, data science, or related experience.

*Skills required: 

  • Must have demonstrated knowledge in Python programming with PyData packages, including Pandas, Numpy and Scipy to perform data analysis. 

  • Must have demonstrated knowledge in SQL programming to query and manipulate data in the database. 

  • Must have demonstrated knowledge in data visualization, creating different kinds of plots to present data research results. 

  • Must have demonstrated knowledge in Git work collaborating with team members on the same project. 

  • Must have demonstrated knowledge with regression and time series analysis, to conduct automated anomaly detection. 

  • Must have demonstrated knowledge with bash programming to schedule different jobs on the cloud server. 

  • Must have demonstrated knowledge in developing and deploying research pipeline under Linux environment and cloud computing platform. 

Must also pass company’s required skills assessment. Employer will accept any amount of professional experience with the required skills.

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