Position Description:
Drives the improvements of systematic trading algorithms to realize low market impact, low cost, and ensure the best execution. Optimizes the implicit and explicit cost of trading decisions based on periodic performance monitoring and review. Merges systematic trading and analytics products and creates platforms that clients can use to navigate and execute in an increasingly complex market. Leads the creation of Cloud platforms to provide real-time and historical Data-as-a-Service (DaaS) to customers. Maintains and ensures the integrity of Transaction Cost Analysis (TCA) database and intelligent modules. Shapes next-generation tools and statistical analysis techniques to improve performance against clients’ trading objectives.
Primary Responsibilities:
Works closely with clients to enhance their trading strategies, educate them on market structure and trading tools, and provide expert consultations to address their unique challenge.
Oversees multi-asset class research and product development across domestic and international equities, and options.
Demonstrates key performance indicators (KPIs) related to revenue and expense, driving the success of both trading strategies and client satisfaction.
Works with product developers, traders, clients, and software developers to deploy electronic trading products and financial services.
Investigates market signals, including price and volume prediction models.
Creates and supports analytical systems used for comprehensive post-trade performance measurement and attribution.
Education and Experience:
Bachelor’s degree in Financial Mathematics, Applied Mathematics, Financial Engineering, Computer Science, Engineering, or a closely related field (or foreign education equivalent) and five (5) years of experience as a Director, Electronic Trading Products (or closely related occupation) building systems and solutions for financial investment or trading decisions, using R, Python, PL/SQL databases, and Artificial Intelligence (AI) and Machine Learning (ML) techniques.
Or, alternatively, Master’s degree in Financial Mathematics, Applied Mathematics, Financial Engineering, Computer Science, Engineering, or a closely related field (or foreign education equivalent) and three (3) years of experience as a Director, Electronic Trading Products (or closely related occupation) building systems and solutions for financial investment or trading decisions, using R, Python, PL/SQL databases, and Artificial Intelligence (AI) and Machine Learning (ML) techniques.
Skills and Knowledge:
Candidate must also possess:
Demonstrated Expertise (“DE”) performing data analytics to improve trading products on Electronic Trading Platforms in a capital markets environments with a Broker Dealer or a Trading Technology Provider, on Regulation National Market System (Reg NMS) equity securities, using KDB+/Q and Python.
DE building quantitative models on trading data, including regression-based market impact and prediction models employing supervised and unsupervised optimization strategies, using Python or Q; modernizing and digitalizing platform products over Amazon Web Services (AWS) for electronic trading experience; reviewing order flow patterns on analytics platform, to tailor custom strategies and reduce trading costs for clients; and conducting A/B tests for hyperparameter tuning and functional enhancements in codebase.
DE working in KDB+ environment to transform and enrich structured and unstructured data for TCA and building purpose-built time-series databases for hypothesis-driven research for algorithmic trading; querying in Q for vectorized data wrangling with large datasets; generating advanced data visualizations and insight using Tableau and computational and plotting libraries in Python; and performing repository management and automation within a Linux environment, using GitHub.
DE providing actionable recommendations for optimizing liquidity access from exchanges, dark pools, dealers, and private rooms through trading algorithms and smart order routers (SOR); and assessing quality and quantity of liquidity provided in trading venues by evaluating normalized performance factors, including risk metrics, toxicity, and counterparty presence, using TCA Database with Python, R, or Q.
Salary: $170,000.00 - $185,000.00/year.
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Please be advised that Fidelity’s business is governed by the provisions of the Securities Exchange Act of 1934, the Investment Advisers Act of 1940, the Investment Company Act of 1940, ERISA, numerous state laws governing securities, investment and retirement-related financial activities and the rules and regulations of numerous self-regulatory organizations, including FINRA, among others. Those laws and regulations may restrict Fidelity from hiring and/or associating with individuals with certain Criminal Histories.
Skills Required
- Bachelor's degree in Financial Mathematics, Applied Mathematics, Financial Engineering, Computer Science, Engineering, or closely related field (or foreign equivalent) and five years of relevant experience, OR Master's degree and three years of relevant experience.
- Experience building systems and solutions for financial investment or trading decisions using R, Python, PL/SQL, and AI/ML techniques.
- Demonstrated expertise performing data analytics to improve trading products in capital markets with a Broker Dealer or Trading Technology Provider, using KDB+/Q and Python.
- Experience building quantitative models on trading data (market impact, prediction models) using Python or Q, including supervised and unsupervised optimization strategies and A/B testing for tuning.
- Experience modernizing and digitalizing platform products on Amazon Web Services (AWS) for electronic trading.
- Experience maintaining and ensuring integrity of TCA databases and building purpose-built time-series databases for algorithmic trading research (KDB+ environment, Q querying).
- Experience generating advanced data visualizations and insights using Tableau and Python plotting libraries.
- Experience with repository management and automation in a Linux environment using GitHub.
- Experience providing actionable recommendations to optimize liquidity access across exchanges, dark pools, dealers, and private venues; assessing venue liquidity quality using TCA with Python, R, or Q; familiarity with smart order routers (SOR).
Fidelity Investments Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Fidelity Investments and has not been reviewed or approved by Fidelity Investments.
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Strong & Reliable Incentives — Bonuses, commissions, and profit-sharing are presented as generous and meaningful components of total compensation, with certain roles achieving high total earnings through multiple pay streams. Variable pay is consistently framed as a positive contributor beyond base salary.
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Retirement Support — A 401(k) match up to 7% alongside additional profit-sharing up to 10% materially enhances long-term compensation. These retirement features are highlighted as standout strengths of the overall package.
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Parental & Family Support — Generous paid parental leave (16 weeks maternity, 12 weeks parental), backup dependent care, and adoption assistance provide robust family support. Hybrid work and caregiving resources further ease family responsibilities.
Fidelity Investments Insights
What We Do
At Fidelity, our goal is to make financial expertise broadly accessible and effective in helping people live the lives they want. We do this by focusing on a diverse set of customers: - from 23 million people investing their life savings, to 20,000 businesses managing their employee benefits to 10,000 advisors needing innovative technology to invest their clients’ money. We offer investment management, retirement planning, portfolio guidance, brokerage, and many other financial products. Privately held for nearly 70 years, we’ve always believed by providing investors with access to the information and expertise, we can help them achieve better results. That’s been our approach- innovative yet personal, compassionate yet responsible, grounded by a tireless work ethic—it is the heart of the Fidelity way.
