Data Scientist

Key Skills

Data Analysis, Data science techniques, Data Visualization, Machine learning techniques, Pandas, Predictive Modeling, Python Programming, R Programming, Statistics

Job Description

Duties: Apply statistical analysis and exploratory techniques to enable the firm’s use of Data Science principles in performing its predictive financial analysis. Utilize knowledge of advanced statistical methods, including distribution analysis, classification, regression, clustering, etc. Deliver financial data metrics, quantitative, statistics-based financial analyses, and visualizations to all functions within the team, including product, design, and business units. Advance the company’s existing quantitative financial and data science initiatives and research opportunities to pursue previously unexplored quantitative financial topics. Research data science methods for financial analysis to create quantitative predictive models that will be used to engineer/develop sophisticated financial investment instruments and tools. Design, engineer, and implement alpha-generative feature sets based on statistical modeling, graph modeling and other Machine Learning Techniques. Collaboratively coordinate all aspects of the data process and research process, including methodology selection, data quality, modeling, and analysis, as well as feature performance evaluation. Develop/engineer statistical models and metrics for insights team and help team make data driven decisions. Work closely with Relationship Managers (RM), Modelers, and Product Managers (PM) and leverage data science and statistical modeling to solve business problems. Engineer and manage data-driven product components such as ranking and recommendation algorithms, which are used by our company to efficiently crowdsource investment insights and subsequently build sophisticated predictive quantitative financial models that drive our financial portfolio construction. Profile signals generated from new programs and datasets.

Minimum education required: Master’s Degree in Computer Science, Mathematics, Statistics, Finance, Economics, Materials Science and Engineering, or related quantitative field.

Minimum experience required: 2 years of experience in Data Science positions.

Skills required: Must have knowledge of the following Data Science skills and technologies: high-dimensional and sparse datasets and ability to combine them (and other statistical metrics) to enhance their value; Statistical methods including Distribution Analysis, Classification, Regression, Clustering, Probabilistic Graphical/Network Modeling methods, Time Series Analysis, Machine Learning techniques, and Causal Inference methods; structured and unstructured data; object-oriented programming in Python; data transformation skills including using Pandas and R; Statistical and Machine Learning techniques including Ordinary Linear Regressions, Non-Linear Regressions, Logistic Regressions, Clustering Analysis, and Dimensionality Reduction techniques; data-driven decision making, observational study, and Casual Inference; and Ranking and Recommendation algorithms. Must also pass company’s required skills assessment.

Base salary: The base pay for this role will be between $165,000 and $300,000 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.