Director, Financial Engineering

Fidelity; Boston (MA); On-site; USD 170,000 - 185,000; Full time

Job summary

Fidelity is seeking an advanced quantitative engineer to design, implement, and optimize trading execution platforms within US equity markets. You will develop models, measure performance, and integrate real-time intelligence to improve execution quality and scalability.

Responsibilities include research design, analytical controls, and deploying ML and optimization techniques. Collaboration with trading and technology teams is essential to deliver best-execution insights across asset classes.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Technology, Information Systems, Financial Technology, or related field, plus six years as Director, Financial Engineering or related role.
• Master’s degree in related field plus two years as Director, Financial Engineering or related role.

Responsibilities

• Lead design of experiments, measurement standards, and analytical controls to improve platforms.
• Define performance frameworks to evaluate and enhance systematic trading platforms.
• Analyze trading/execution data to reduce costs and improve outcomes.
• Develop methods to assess market conditions on platform performance and decisions.
• Translate research into scalable platform improvements via Agile methods.
• Evaluate execution quality and adjust methodologies based on insights.
• Apply ML models to optimize execution and minimize market impact.
• Lead DeFi analysis and collaborate with teams to deliver scalable capabilities.

Skills

Python

KDB/Q

ML algorithms

Transaction cost analysis

Quant forecasting

Optimization models

Linear programming

Statistical analysis

Hypothesis testing

Bootstrap

Education

Bachelor’s degree in Computer Science/Engineering/IT or related field

Master’s degree in related field (optional)

Tools

scikit‑learn

Vowpal Wabbit

AWS

Job description

Fidelity will not provide immigration sponsorship for this position.

Job Description:

Note: Fidelity will not provide immigration sponsorship for this position.

Position Description:

Generates insights from historical and real-time data using Python and KDB/Q to assess cost of trading, constructing cost models and conduct transaction cost analysis, evaluating execution quality, and developing systematic algorithm selection framework. Designs and advances systematic trading platforms within U.S. equity markets, integrating real-time intelligence into optimized execution strategies. Leads the development of models, performance measurement systems, and analytical frameworks that enhance execution quality, scalability, and performance across diverse client objectives. Develops optimization framework that improve execution quality given flow complexion and dealer competitions in equity and options. Conducts market structure, liquidity, and venue behavior research using public data, leveraging cloud-based virtual machines in Amazon Web Services (AWS) for analysis.

Primary Responsibilities:

• Leads research on experimental design, measurement standards, and analytical controls to drive continuous platform improvement.
• Defines performance frameworks to evaluate systematic trading platforms and inform strategic enhancements.
• Analyzes trading and execution data to identify opportunities, reduce transaction costs, and improve customer outcomes.
• Develops analytical methods to assess the impact of market conditions on platform performance and operational decision-making.
• Translates quantitative research findings into scalable platform improvements through Agile development processes.
• Evaluates execution quality and post-trade performance trends, recommending changes to methodologies or workflows based on analytical insights.
• Applies statistical and machine learning (ML) models to optimize execution algorithms, enhance trading performance, and minimize market impact.
• Leads research on market structure, routing logic, liquidity dynamics, and client behavior to inform execution strategy.
• Develops prototypes and analytical tools to assess broker performance and generate strategic insights.
• Collaborates with trading, order flow management, and technology teams to strengthen analytical capabilities and improve best-execution outcomes across asset classes.
• Analyzes decentralized finance (DeFi) protocols and partners with business, product, and technology teams to deliver scalable capabilities within the DeFi ecosystem.

Education and Experience:

Bachelor’s degree in Computer Science, Engineering, Information Technology, Information Systems, Financial Technology, or a closely related field (or foreign education equivalent) and six (6) years of experience as a Director, Financial Engineering (or closely related occupation) performing transaction cost analysis in US markets and analyzing historical trading data using KDB/Q and Python.

Or, alternatively, Master’s degree in Computer Science, Engineering, Information Technology, Information Systems, Financial Technology, or a closely related field (or foreign education equivalent) and two (2) years of experience as a Director, Financial Engineering (or closely related occupation) performing transaction cost analysis in US markets and analyzing historical trading data using KDB/Q and Python.

Skills and Knowledge:

Candidate must also possess:

• Demonstrated Expertise developing ML algorithms and quantitative forecasting tools including retail volume forecast, equity contextual trading algorithm selection, and fixed income municipal new issuance pricing using Python, KDB/Q, scikit‑learn (SK Learn), and Vowpal Wabbit; and conducting transaction cost analysis and algorithm selection using KDB/Q, leveraging cloud based virtual machines in AWS for analytical workflows.
• Demonstrated Expertise influencing dealer pricing and execution decisions using optimization models based on linear programming, implemented in KDB/Q and Python; and conducting simulations to project dynamics of market markers under varying market constraints using KDB/Q and python.
• Demonstrated Expertise performing statistical analysis of execution results using hypothesis testing techniques, including t-tests, analysis of variance (ANOVA), and non-parametric methods including Wilcoxon signed-rank and Mann–Whitney U tests; and applying bootstrap resampling techniques to detect information leakage, assess performance differences, and validate cost model stability through confidence intervals.
• Demonstrated Expertise conducting DeFi analysis by examining blockchain ecosystem architecture, gas-fee economics, and decentralized exchange models including automated market makers (AMMs) and liquidity aggregators; and validating on-chain data and supporting decentralized finance research through analysis of token issuance mechanisms.

Salary: $169,986.00 to $185,000.00/year.

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Fidelity’s Onsite Working Model
Fidelity is transitioning to a full-time onsite working model through a phased rollout across regions and roles. Currently, some roles and locations require 100% onsite presence, while others require less. Onsite expectations are likely to evolve as the rollout continues. This transition does not apply to fully remote roles.

Certifications:

Category:

Capital Markets Product

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.