Principal Quant Developer

Fidelity Investments • Boston, MA

6d • $107,000 - $216,000

About The Position

Fidelity's Quantitative Research & Investing Technology (QRIT) team within Asset Management Technology is seeking a Principal Quantitative Developer to support researchers in prototyping and delivering systematic investment strategies. The role contributes high-impact technology solutions across alpha research, portfolio construction, and risk management. It requires full-stack software engineering expertise, particularly in Python and PL/SQL databases, and a commitment to building high-quality, scalable, robust, resilient, and efficient analytical and software solutions.

The Quant Development team partners with Asset Management's Advance Strategies and Research team on systematic investment strategies, portfolio construction, risk management, alpha research, and GenAI. Its solutions are used to improve Asset Management's efficiency and decision-making processes. The position involves working closely with quantitative researchers and investment teams throughout the development lifecycle.

Requirements

• Bachelor's degree in Computer Science, Financial Engineering, Information Technology, Information Systems, Mathematics, Physics, Statistics, Engineering, or a closely related field, and six years of experience as a Senior Quant Developer or in a similar role; alternatively, a Master's degree or equivalent foreign education in one of these fields and four years of experience as a Lead Quantitative Development professional or in a similar role.
• Experience building high-quality, robust, and efficient systems and solutions for financial investment decisions using Python, PL/SQL databases, and quantitative techniques.
• Expert Python skills and experience across the development stack.
• Exposure to object-oriented programming and design patterns.
• Experience with at least one unit-testing framework and understanding of test-driven development concepts and methodologies.
• Strong demonstrable knowledge of mathematics, statistics, and quantitative finance.
• Deep understanding of quantitative techniques and methods, statistics, and econometrics, including probability, linear regression, and time-series data analysis.
• Domain knowledge in equities, fixed income, or alternative asset classes.
• Proven track record delivering production quantitative solutions in a systematic investing or trading environment.
• Skilled in SQL databases, including Oracle.
• Skilled in batch and API technologies, such as batch scheduling and REST API development.
• Proven ability to construct and manage robust data pipelines and event-driven workflows.
• Expertise in system design and AWS cloud architecture.
• Experience with Docker containerization.
• Experience implementing CI/CD pipelines using Linux and Jenkins, and code versioning using GitHub.
• Experience with infrastructure-as-code methodologies.
• Strong communication and problem-solving skills, with the ability to partner effectively with quantitative researchers and investment teams.

Nice To Haves

• Working knowledge of R.
• Experience with industry-scale optimization libraries such as Gurobi, CPLEX, Axioma, or SciPy, and portfolio construction or optimization.
• Progress toward the CFA designation or equivalent.
• Experience with Snowflake, NoSQL, or graph databases.
• Experience with batch scheduling tools such as Autosys and Airflow, and REST API frameworks such as FastAPI and Flask.
• Experience with Docker orchestration using Kubernetes.
• Familiarity with observability and production support, including logging, tracing, monitoring, and alerting.
• Experience operationalizing ML models and pipelines on AWS using SageMaker and Bedrock, including training, deployment, model registry, monitoring, foundation-model access, and fine-tuning.
• Familiarity with experiment-tracking and model-versioning tools such as MLflow.
• Experience applying machine learning to quantitative investing, including time-series forecasting, anomaly detection, and predictive analytics.
• Experience deploying and operationalizing LLM-based or agentic workflows in production, including tools such as LangGraph and LangChain.
• Awareness of responsible AI governance practices.

Responsibilities

• Support researchers in prototyping and delivering systematic investment strategies.
• Develop technology solutions for alpha research, portfolio construction, and risk management.
• Analyze and design Python systems implementing quantitative models for systematic financial investments, including time-series forecasting, multi-asset-class portfolio construction, risk management, alpha research, and simulation-based algorithms.
• Construct and manage robust data pipelines and event-driven workflows.
• Design systems and cloud architectures on AWS.
• Implement CI/CD pipelines and infrastructure-as-code methodologies.
• Operationalize machine-learning models and pipelines on AWS, including their production lifecycle.
• Collaborate with quantitative researchers and investment teams to deliver solutions through the full development lifecycle.

Benefits

• Comprehensive health care coverage.
• Emotional well-being support.
• Market-leading retirement benefits.
• Generous paid time off.
• Parental leave.
• Charitable giving employee match program.
• Educational assistance, including student loan repayment, tuition reimbursement, and learning resources.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal