Position Description:
Develops models and performs financial analysis to evaluate trading tools for systematic trading processes within relational databases, using programming tools (Python, KDB/Q, R, MATLAB, JAVA, SQL, and C++). Develops analytics and visualizations, offline and in real-time, using Tableau. Drives the core capabilities of a systematic trading effort through data analysis, model building, and by developing and coding trading strategies. Implements mathematical modeling applied to trading for post-trade analysis and strategy development. Collaborates with traders, quantitative analysts, data scientists, and developers/engineers to advance systematic trading efforts in Equity markets.
Primary Responsibilities:
Develops processes for the handling and storage of financial data used in systematic trading. Supports and participates in quantitative efforts on the trading desk. Develops new tools and capabilities to solve novel problems facing the trading desk. Creates charts and graphs to illustrate technical reports. Contributes to the design and development of automated systematic trading systems. Employs financial models to develop solutions to financial problems or to assess the financial impact of transactions. Informs investment decisions by analyzing financial information to forecast business, industry, or economic conditions. Interprets data on price, yield, stability, future investment-risk trends, economic influences, and other factors affecting investment programs.Education and Experience:
Bachelor’s degree (or foreign education equivalent) in Business Administration, Business Analytics, Computer Science, Engineering, Finance, Information Systems, Management, or a closely related field and six (6) years of experience as an Equity Trader II (or closely related occupation) developing models and performing quantitative analysis in support of the systematic trading effort using programming tools (Python, KDB/Q, R, SQL, and Tableau) and large scale structured and unstructured data.
Or, alternatively, Master’s degree (or foreign education equivalent) in Business Administration, Business Analytics, Computer Science, Engineering, Finance, Information Systems, Management, or a closely related field and four (4) years of experience as an Equity Trader II (or closely related occupation) developing models and performing quantitative analysis in support of the systematic trading effort using programming tools (Python, KDB/Q, R, SQL, and Tableau) and large scale structured and unstructured data.
Skills and Knowledge:
Candidate must also possess:
Demonstrated Expertise (“DE”) designing and building decision support tools, mathematical models and recommendations for improving investment trading process; generating pre-trade and post-trade analytics, transactional cost analysis (TCA) metrics to evaluate trading performance and underlying factors that drive trading costs for US, Europe, and Asia using extensive internal data and external market data; and leveraging tools — KDB/Q, SQL, Tableau, Snowflake, and Excel. DE developing quantitative metrics, conducting advanced analysis, developing detail-oriented visualizations for analyzing and/or evaluating trading systems, processes using KDB/Q, Tableau, Snowflake, Python, SQL, and Oracle; automating data generation process, identifying and alerting of data quality issues; and undertaking ad hoc analysis in timely manner on extensive set of subject areas for internal or external reporting purposes. DE performing full-stack systems analysis, design and development of complete analytical platforms — gathering requirements, documentation, performing data mining, functional design, required coding for data generation, developing the visualization — using large scale data hosted in Snowflake or Oracle by creating and managing data generation process in KDB/Q, Python, Snowflake — Snowflake tables, views, and stored procedures; and working across teams to collaborate hosting code or applications on shared technology stack. DE leading and collaborating with Trading and Asset Management technology groups on large scale data projects which directly relate to everyday functioning of quantitative analysts and the larger equity trading organization with at most importance on data quality; and continuously educating and enabling technology partners for long term stability in data systems.#PE1M2
Certifications: