Duties: Perform quantitative, data-driven research and data analysis and apply statistical modeling techniques to design and implement granular domain-specific indicators from data to detect and analyze statistical patterns in large unstructured datasets, relating them to company, industry, and macroeconomic factors. Perform exploratory data analysis and research, formulate, design, and develop predictive quantitative statistical models for equities and other asset classes. The resulting models will be capable of processing vast amounts of data for a variety of phenomena, which will drive informed, data-driven investment decisions. Perform and use computer science data research and analysis to assist in generating a series of economic insight research reports relating trends. Build quantitative models for equities and generate a series of economic insight research reports relating trends in our data indicators and predictions to investment themes. Collaboratively manage and improve all aspects of the data process and research process, including methodology selection, data collection and quality, modeling and analysis, and performance monitoring. Write production-level Python code to author pipelines. 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 Data Science, Statistics, Mathematics, Computational Finance, or related field. Position does not require specific years of experience but requires listed skills.

Skills required: Must have demonstrated knowledge of querying relational databases. Must have demonstrated knowledge of big data technologies stack including Spark and SQL. Must have demonstrated knowledge of parallel processing algorithms, methods, and infrastructure. Must have demonstrated knowledge of CPU and GPU cloud infrastructure including AWS and developing Data Definition Language scripts to query SQL databases efficiently. Must have demonstrated knowledge of data visualization tools including Matplotlib and Seaborn. Must have demonstrated knowledge of data manipulations and exploratory data analysis in Python. Must have demonstrated knowledge of Machine Learning and statistical techniques in Python. Must have demonstrated knowledge of using Git in a production environment with multiple users. Must have demonstrated knowledge of performing object-oriented computations in Python, including designing and implementing data analytics systems in Python. Must have demonstrated knowledge of Regression and time series analysis to conduct quantitative research, and command line programming to schedule different jobs on the cloud server. Must have demonstrated knowledge of performing quantitative research using structured data and data science best practices. Must have demonstrated knowledge of developing and deploying research pipeline under cloud computing platform. Must have demonstrated knowledge of financial analysis and modeling. Must pass company’s required skills assessment. Employer will accept any amount of experience with the required skills.

The base pay for this role will be between $165,000 and $325,000 per year. This role may also be eligible for other forms of compensation and benefits, such as a discretionary bonus, health, dental and other wellness plans and 401(k) contributions. Discretionary bonus can be a significant portion of total compensation. Actual compensation for successful candidates will be carefully determined based on a number of factors, including their skills, qualifications and experience.