This role pays less than
88%
of similar roles. Most pay
$176,012–$234,710
— the shaded band above.
At the midpoint, this role pays about
$160k
versus about
$205k
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
84 open roles
on FindRole.
Listed pay typically runs
$126,000–$199,592
across 21 roles with salary data.
The Principal Quantitative Developer joins the team to design and develop investment risk analytics platforms focused on alternative investment products. This role involves building linear and non-linear risk analytics for model calculation, validation, and stress analysis of portfolios and derivative instruments. The developer will create reporting processes for derivative exposure measurement, leverage risk monitoring, and Value at Risk analysis while preparing large-scale datasets using statistical techniques. Key responsibilities include partnering with portfolio managers to deliver data-driven solutions and implementing automated workflows for performance analytics. The role requires expertise in Python, R, SQL, Snowflake, Git, and APIs, alongside experience with MSCI RiskMetrics and MSCI Barra. Candidates will also utilize Power BI for visualization and develop tools to analyze market, credit, liquidity, and derivative risks within an investment management context to support risk decision-making.
Design and develop risk analytics platforms for quantitative modeling of alternative investment products.
Develop and maintain linear and non-linear risk models to support calculation, validation, and stress analysis.
Create Python and SQL based tools to calculate portfolio-level risk measures and monitor derivative exposure.
Build automated reporting dashboards and visualization solutions to communicate risk metrics to senior leadership.
Extract, cleanse, and transform large-scale financial datasets from internal and external sources using SQL and Snowflake.
Validate and back-test portfolio and derivatives risk models against historical outcomes and benchmarks.
Implement automated data quality controls and reproducible pipelines for risk modeling and auditability.
Develop automated workflows and batch processing to support trading system testing and operational readiness.
What we're looking for
Bachelor's degree in a quantitative field and experience as a Principal Quantitative Developer or equivalent.
Master's degree in a quantitative field and experience as a Principal Quantitative Developer or equivalent.
Experience performing quantitative and analytical evaluation of portfolio and derivative risk models within an investment management or trading environment.
Expertise validating and back testing risk models using Python, R, and SQL.
Proficiency in calibrating model parameters for market and derivatives risk measures including Greeks, expected shortfall, and liquidity risk.
Experience producing Monte Carlo-based risk metrics and stress testing outputs using Python and MSCI RiskMetrics.
Experience designing risk reporting, interactive dashboards, and visual analytics using Python, R, and Power BI.
Expertise in extracting, cleansing, and transforming large scale financial data using SQL, Snowflake, Python, and APIs.
C++
Java
Python
kdb+/q
SQL
CUDA
OpenCL
Boost
QuantLib
NumPy
Pandas
Linux
Git
CI/CD
Monte Carlo Simulations
Finite Difference Methods
Stochastic Calculus
Jira