Director of Systematic Trading Quant merging systematic trading and analytics products for Fidelity Capital Markets clients. Leading product evolution and improving trading algorithms with data-driven strategies.
Responsibilities
merge our systematic trading and analytics products and create a platform that Fidelity Capital Markets clients can use to navigate and execute in an increasingly complex market
Focus on evolving products in Fidelity Capital Markets equity offering towards our integrated platform vision
Improving trading algorithms (VWAP, LSA, IS, Dark, etc.) to achieve best execution for our clients
Building and deploying machine learning models through production cycle
Conducting performance review, continually validating models in production, examining A/B test results, and proposing new strategies to improve performance of algorithms
Staying on top of market structure and deriving ways to optimize the use of new liquidity sources
Creating tools, prototypes and simulation engines to streamline processes and test new ideas
Working closely with business, trading consultants, product and technology teams to improve product offering
Requirements
A Master’s or Ph.D. degree with experience in Engineering, Computer Science, Applied Mathematics or other relevant quantitative discipline
Three year experience in systematic trading and Transaction Cost Analysis (TCA)
Experience with coaching large language model for quantitative analysis
Series 7 and 57 to be obtained within a time frame set by the business unit
Your ability to analyze vast amount of data and optimize outcomes of a complex trading system
Your in-depth data science, machine learning and analytical knowledge to let data tell stories
Your mastery of artificial intelligence to conduct transaction cost and other quant analyses
Your eagerness to optimize workflow, create scale and efficiency and learn new things
Your delight in data and influence through thought leadership using verbal and written communication
Your knowledge of US Equity market, trading algorithms and market microstructure
Your technical knowledge in Python, KDB/Q, Snowflake and MCP.
Benefits
comprehensive health care coverage
emotional well-being support
market-leading retirement
generous paid time off
parental leave
charitable giving employee match program
educational assistance including student loan repayment
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