Duties: Design and implement granular domain-specific indicators based on computer data research and analysis, relating them to company, industry, and macroeconomic factors. Build quantitative models for equities and other asset classes and generate a series of economic insight research reports relating trends in our data indicators and predictions to investment themes. Perform and use computer science data research and analysis to assist in generating a series of economic insight research reports relating trends in our data indicators and predictions to investment themes. Collaboratively manage all aspects of the data process and research process, including methodology selection, data collection and quality, modeling and analysis, as well as performance monitoring. Research and manage requirements for a set of dependent computer science-based data products derived from a large portfolio of integrated computer data research feeds. Perform computer science data research that contributes to our data sourcing strategy across multiple industry data verticals supporting our prediction efforts.
Minimum education and experience required: Master’s degree or equivalent in Computer Science, Statistics, Economics, Data Science, or related field plus 3 years of experience as a Data Scientist, Data Analyst, or related experience OR Bachelor’s degree or equivalent in Computer Science, Statistics, Economics, Data Science, or related field plus 5 years of experience as a Data Scientist, Data Analyst, or related experience.
- Must have experience in statistical analysis of financial data including trend modelling and outlier detection.
- Must have experience in working with both structured and unstructured data.
- Must have experience in big data technologies, such as Hadoop and Spark.
- Must have demonstrated knowledge in Object Oriented programming in both Java and Python including ability to design and implement data systems in these languages.
- Must have experience in designing and implementing relations and constraints in relational database systems, including ability to optimize queries with indexes, and develop Data Definition Language scripts to query SQL Databases efficiently.
- Must have demonstrated knowledge of Statistical and Machine Learning techniques (including but not limited to Ordinary Linear Regressions, Non-Linear Regressions and Time Series Analysis).
- Must have experience in developing and implementing high-performance and robust numerical simulations in a production environment.
- Must have experience in data engineering and ETL development. Must have demonstrated knowledge of the Linux operating system.
- Must have demonstrated knowledge in shell scripting.
- Must have experience using a distributed version control system such as Git or Mercurial in a production environment with multiple users.
Must also pass company’s required skills assessment.
Employer will accept any amount of professional experience with the required skills.