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Added 1 min ago
Senior Transmission Planning Engineer - Stability Studies
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…technically rigorous power system studies and strategic planning support to utilities, developers, and grid operators navigating one of the most dynamic periods in the history of the…
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Lead Energy Engineer
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Senior Software Developers in Test (Java, Selenium)
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Paid Time Off and Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well-being.
Added 1 min ago
Application Support Engineering - SRE
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Added 3 mins ago
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Added 5 mins ago
Engineer III
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Engineer I
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Added 7 mins ago
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Added 7 mins ago
Azure DevOps Engineer
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Added 11 mins ago
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Senior Dynatrace Observability Engineer / Subject Matter Expert (SME)
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Added 20 mins ago
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Added 20 mins ago
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Added 21 mins ago
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Added 21 mins ago
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Fidelity Technology Group, LLC

Principal Quant Developer

Boston, MA, United States

$107,000 to $216,000 USD / year

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Job details

Pay: $107,000 to $216,000 USD / year
Posting language: English
Posted: Nov 2, 2026

Original job description

Fidelity will not provide immigration sponsorship for this position.

Job Description:

The Role The Quantitative Research & Investing Technology (QRIT) team within Fidelity's Asset Management Technology group is seeking a highly motivated and curious Principal Quantitative Developer. In this role you will contribute to a dynamic and fast-paced development team supporting researchers in prototyping and delivering new systematic investment strategies. You will provide high impact solutions on various projects including alpha research, portfolio construction, and risk management. Your technology knowledge covers a broad spectrum of technologies, including Python and PL/SQL databases, positioning you as a full-stack software engineer who capitalizes on enterprise technology. You are committed to constructing high-quality, scalable, robust, resilient and efficient analytical and software solutions that propel investment processes forward.

The Expertise and Skills You Bring

A Bachelor's degree in Computer Science, Financial Engineering, Information Technology, Information Systems, Mathematics, Physics, Statistics, Engineering, or a closely related field and six (6) years of experience as a Senior Quant Developer or similar role.
Alternatively, a Master's degree (or equivalent foreign education) in the same fields, accompanied by four (4) years of experience as a Lead Quantitative Development or similar role.
This experience should include building high-quality, robust, and efficient systems and solutions for financial investment decisions, utilizing Python, PL/SQL databases, and quantitative techniques.

Core Engineering

Expert in Python with experience across the development stack (full stack)
Exposure to object-oriented programming (OOP) and design patterns
Experience in at least one unit testing framework and understanding of test-driven development (TDD) concepts and methodologies
Working knowledge of R is a plus

Quantitative & Domain Knowledge

Strong, demonstrable knowledge of mathematics, statistics, and quantitative finance (core to this role)
Deep understanding of quantitative techniques and methods, statistics and econometrics including probability, linear regression and time series data analysis
Analyze and design systems to implement quantitative models for systematic financial investments using Python, including time series forecasting models, multi-asset class portfolio construction strategies, risk management tools, alpha research, and simulation-based algorithms
Domain knowledge in either equities, fixed income or alternative asset classes
Proven track record of delivering production quant solutions in a systematic investing or trading environment
Experience with industry-scale optimization libraries (e.g., Gurobi, CPLEX, Axioma, SciPy) and portfolio construction / optimization is a strong plus
Progress towards CFA (or equivalent) a plus

Data & Infrastructure

Skilled in SQL databases (Oracle); Snowflake, NoSQL, or Graph databases a plus
Skilled in batch and API technologies: such as batch scheduling (using Autosys and Airflow) and creating REST APIs (using FAST API and Flask)
Proven ability to construct and manage robust data pipelines and event-driven workflows
Proven expertise in system design and cloud architecture on AWS, leveraging resources including Lambda, S3, EKS, and EC2

DevOps & CI/CD

Experience in containerization with Docker; orchestration with Kubernetes a plus
Implement CI/CD pipelines (using Linux and Jenkins), code versioning using GitHub
Experience in Infrastructure as Code methodologies for consistent and scalable infrastructure management
Familiarity with observability and production support (logging, tracing, monitoring, alerting) a plus

MLOps & AI (Preferred)

Operationalizing ML models and pipelines on AWS using modern MLOps principles, including SageMaker (training, deployment, model registry, monitoring) and Bedrock (foundation model access, fine-tuning) and production lifecycle management
Familiarity with experiment tracking and model versioning tools (e.g., MLflow)
Applying ML to quantitative investing: time series forecasting, anomaly detection, and predictive analytics
Deploying and operationalizing LLM-based / agentic workflows in production (e.g., LangGraph, LangChain), including orchestration, tool use, monitoring, and evaluation
Awareness of responsible AI governance practices

Collaboration & Communication

Strong communication and problem-solving skills; partners effectively with quant researchers and investment teams to deliver solutions through the full development lifecycle

The Team The Quant Development team is part of Asset Management's Quantitative Research & Investment Technology group. We partner with Asset Management's Advance Strategies and Research team on cutting edge projects including systematic investment strategies, portfolio construction, risk management, alpha research, and GenAI. We build high quality, robust, and highly-scalable solutions that are used to improve Asset Management's efficiency and decision-making processes.

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.

The base salary range for this position is $107,000-216,000 USD per year. Placement in the range will vary based on job responsibilities and scope, geographic location, candidate’s relevant experience, and other factors.

Base salary is only part of the total compensation package. Depending on the position and eligibility requirements, the offer package may also include bonus or other variable compensation.

We offer a wide range of benefits to meet your evolving needs and help you live your best life at work and at home. These benefits include comprehensive health care coverage and emotional well-being support, market-leading retirement, generous paid time off and parental leave, charitable giving employee match program, and educational assistance including student loan repayment, tuition reimbursement, and learning resources to develop your career. Note, the application window closes when the position is filled or unposted. 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.

Certifications:

Category:

Information Technology

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More about this job

Skills

Research
Risk management
Python
Oracle PL/SQL
Computer science
Financial engineering
Computer technology
Statistics
Object-oriented programming
Unit testing
Data analysis
Forecasting
SciPy
CFA
SQL
Oracle
Snowflake
NoSQL
Scheduling
Apache Airflow
API development
FAST
Flask
AWS
DevOps
CI/CD
Docker
Kubernetes
Linux
Jenkins
GitHub
Infrastructure as code
ML
Mlflow
LangChain
Collaboration
Communication skills
Problem solving
Decision making
Securities

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