Quantitative Research and Investments (QRI) is seeking a highly motivated data expert in the domain of portfolio risk analytics to join a risk platform operations team responsible for ensuring that all vendor and internal portfolio risk analytics used for risk management and portfolio construction across Fidelity are delivered consistently, accurately and on a timely basis.

The Risk Platform Operations team are the stewards of risk analytics data for Fidelity Asset Management. They focus on quality control of all data that feeds into portfolio risk analytics, including security factor exposures and proxies, factor returns and covariance matrices, fundamentals data, security T&Cs, and portfolio holdings.

In this role, you will utilize domain expertise necessary to root-cause daily issues effectively, work with internal and external data providers to resolve issues at source, answer portfolio and risk manager questions, and develop automated systems for identifying data quality issues.

The Skills and Expertise You Bring:

• You bring a unique blend of technical acumen, analytical depth, and domain expertise that enables Fidelity Asset Management to make informed, data-driven investment decisions. Your work ensures the integrity, accuracy, and timeliness of risk analytics and data operations, directly supporting portfolio construction and risk management.

• Act as a steward of data assets critical to risk management and portfolio construction.

• Lead quality service efforts to address overnight data feed issues, enabling fast, seamless responses to upstream problems and insulating production and research teams.

• Update and verify multi-factor risk model inputs and outputs prior to client delivery.

• Ensure access to accurate, timely, and relevant portfolio risk analytics by collaborating with technology and business partners to resolve data quality issues at the source.

• Analyze systems and processes to identify efficiencies and improve reporting accuracy and timeliness.

• Apply experience with market risk models from vendors such as Barra, Axioma, Northfield, or Bloomberg.

• Leverage strong analytical skills to comprehend large datasets and implement effective quality controls.

• Operate with a proactive, self-motivated approach, meeting objectives with minimal direction.

• Utilize vendor-provided risk data and tools including Bloomberg PORT, BarraOne, RiskManager, and/or Axioma.

• Demonstrate deep knowledge of financial data across security, company, portfolio, and index levels, including pricing for equities, bonds, and derivatives.

• Employ technical proficiency in SQL, Python, Snowflake, and/or Oracle, along with data quality frameworks.

• Hold a Bachelor’s degree (or higher) in mathematics, statistics, engineering, computer science, finance, or a related quantitative field.

• Bring 3+ years of experience in global data operations or support teams within peer firms, with a proven track record of delivering value.

• Apply expertise in anomaly detection methods, data quality workflows, and statistical best practices.

• Communicate effectively across technical and investment teams.

• Navigate complex data environments and support the necessary technology and analytics infrastructure.

• Identify root causes of data quality issues and collaborate with teams and providers to resolve them.

• Create automated processes to detect errors and ensure high-quality data for investment decision-making.

• Document procedures and validate data to maintain transparency and reliability.

• Possess domain expertise in investment management across risk management, portfolio management, trading, and investment operations.

The Team:

The Risk Platform Operations team is an integral part of the Quantitative Research and Investing (QRI) division in Asset Management. QRI is responsible for the management and development of quantitative investment strategies and solutions while providing high quality quantitative, data-driven support to Fidelity’s fundamental investment professionals, ensuring they have access to the most relevant data and advanced quantitative analysis.