Quantitative Risk Developer

Fidelity Financial Services

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Quick summary

Work type: On-site
Location: Boston, MAJersey City, NJ
Salary: $100,000–$200,000 / yr
Posted: 4 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $189k

This role $150k

$84k $251k

below market most similar roles pay here above market

This role pays less than 72% of similar roles. Most pay $143,560–$234,800 — the blue band above. At the midpoint, this role pays about $150k versus about $189k for comparable roles.

Based on 240 similar postings.

Employer

About Fidelity Financial Services

Fidelity Investments is one of the largest financial services companies in the world, offering brokerage services, mutual funds, retirement planning, wealth management, and life insurance to individuals and institutions. Industry: Financial Services & Investment Management

Fidelity Financial Services currently has 157 open roles on FindRole.

Listed pay typically runs $107,000–$216,000 across 42 roles with salary data.

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View all roles at Fidelity Financial Services

At a glance

TL;DR · Quantitative Risk Developer

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The Quantitative Risk Developer joins the Quantitative Research and Investments team to build a next-generation portfolio analytics platform. This greenfield project serves investment professionals for risk management, portfolio construction, and alpha research across various asset classes. The developer will design and implement core risk capabilities, including multi-asset class ex-ante risk modeling, performance attribution analysis, and stress testing. Key responsibilities involve writing core portfolio analytics libraries, optimizing run-time performance, and ensuring seamless integration with production environments. The role requires expert Python programming using NumPy and SciPy, along with Git proficiency, testing methodologies, and code reviews. Candidates should understand AI/ML fundamentals for time series anomaly detection and have experience with interactive Python GUIs like Dash or Streamlit to solve complex quantitative risk and portfolio construction problems.

Skills

Python NumPy SciPy Git Dash Streamlit AI ML Code Review Data Infrastructure Portfolio Construction Risk Modeling

What you'll do

Design and implement core risk capabilities for the risk management platform.
Develop multi-asset class ex-ante risk models and performance attribution analysis.
Build stress testing and scenario analysis tools for portfolio management.
Write core portfolio analytics libraries using Python, NumPy, and SciPy.
Optimize platform run-time performance, scalability, and robustness using software best practices.
Integrate the quantitative codebase with existing systems and production data infrastructure.
Build interactive Python GUIs using frameworks like Dash or Streamlit.
Apply AI and ML techniques for time series data anomaly detection.

What we're looking for

Master’s degree in a technical field like science, engineering, or mathematics with 5+ years of experience as a quant developer for an investment firm.
Bachelor’s degree with 7+ years of relevant experience may be considered.
Expert Python programming skills with a strong emphasis on libraries used in quantitative finance, including NumPy and SciPy.
Experience implementing quantitative models and applications for risk management or portfolio construction (preferred).
Good understanding of software version control with strong Git proficiency, testing methodologies, code reviews, and documentation.
Understanding of AI/ML fundamentals and experience applying AI techniques for time series data anomaly detection.
Practical experience building interactive Python GUIs such as Dash or Streamlit (preferred).
Strong communication skills to convey complex technical information to both technical and non-technical audiences.

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