Equity Quant Trader [Multiple Positions Available]

Work as a quantitative trader on the US Program Trading (PT) Risk team. Handle the trading and risk management of index rebalancing and special situation strategies. Build systematic index prediction models to anticipate Index Rebalancing events. Test indicators on various dataset integrating advanced quantitative technics. Define quantitative process to trade strategies in a systematic framework, leveraging algo-trading capabilities. Monitor automated processes for program trade execution. Utilize portfolio construction principles to reduce factor risks through optimization technics. Integrate performance analytics into program trading infrastructure to improve its efficiency. Interact with trading, sales teams, and clients across the Equities division and engage with the Program Trading (PT) sales team on facilitating client trades, generate content and trading commentary. Forecast index related expected flow and associated market impact. Conduct active risk management and taking appropriate trading decisions to keep the risk profile of the business inline with the policy.

Minimum education and experience required: Bachelor's degree in Statistics, Computer Science, Finance, Economics, or related field of study plus 3 years of experience in the job offered or as Equity Quant Trader, Equity Portfolio Trading, or related occupation.

Required: This position requires three (3) years of experience with the following: Utilizing sell-side quantitative trading techniques, including algorithmic trading and model-driven portfolio trading, in support of large-scale trading strategies, such as index rebalancing or other liquidity events, to balance liquidity and risk factor exposures, achieve cost-efficient implementation and enhance overall trading performance and revenue generation. This position requires two (2) years of experience with the following: Building systematic index prediction models including Python and KDB from diversified and thematic US index providers for scheduled events and special situations; building systematic and dynamic backtest in python and KDB on index strategies; utilizing statistical modeling including linear and logistic regression to perform alpha research, turnover reduction, market impact analysis, automatic pricing engine parameter calibration, clients tiering and generate reports on key performance metrics; utilizing Barra risk models and Minimum Variance Optimization models to reduce the risk of the portfolio; developing and backtesting systematic, end to-end, statistical arbitrage trading and quantitative event-driven strategies, independent of index rebalancing; utilizing KDB to build automated process to read, parse and store large scale index constituents data from Secure File Transfer Protocol (SFTP) sites; building interactive dashboards using JavaScript for data visualization and report generation; Developing using python, monitoring, and configuring algorithmic trading systems; Initiating and implementing systematic checks using Python to prevent system breaks; Author, publish, distribute research and commentary around index changes events to clients and sales, advising clients on trading opportunities and index inclusion. Job Location: 270 Park Avenue, New York, NY 10017. Full-Time. Salary: $260,000 - $285,000 per year.