Associate, Quantitative Data Operations
About The Position
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.
Requirements
- Experience with market risk models from vendors such as Barra, Axioma, Northfield, or Bloomberg
- Highly analytical with the ability to quickly comprehend large data sets, develop and implement the right quality controls for these datasets
- Highly proactive and self-motivated with the ability to meet objectives under minimal direction
- Experience with vendor-provided risk data and capabilities, including Bloomberg PORT, BarraOne, RiskManager and/or Axioma
- Experience in security, company, portfolio, and index-level information used in financial industry, including pricing for various security types (equities, bonds, derivatives) and construction of holdings
- Experience in SQL, Python, Snowflake and / or Oracle and related tools and DQ frameworks
- Bachelor’s degree (or higher) in mathematics, statistics, engineering, computer science, finance, or another quantitative field
- 3+ years’ experience in global data operations and/or support teams in peer firm(s) with a demonstrable track record delivering the value described for this role
- Experience with methods, tools, statistics, and best practices for autonomous and discretionary anomaly detection, and data quality workflow
- Excellent written and verbal communication skills; experience working with both technical and investment teams
- Proven track record of working with complex data environments and associated technology and analytics infrastructure needed to support these environments
- Demonstrated ability to root-cause data quality issues in complex environments and work with other teams and data providers to correct issues at source
- Experience in creating automated processes to identify errors to ensure high quality of data to support the investment process
- Experience in documenting essential procedures and calculations, and validating data
- Investment Management business domain expertise across some combination of risk management, portfolio management, trading and investment operations
Responsibilities
- Act as a steward of data assets used in risk management and portfolio construction
- Manage a quality services effort to respond to data quality issues in overnight feeds, enabling fast and seamless responses to upstream issues and insulating production and research from them
- Update and verify the multi factor risk model inputs and outputs before delivery to clients
- Enable Fidelity Asset Management’s access to accurate, timely and relevant portfolio risk analytics, working closely with key technology and business partners to correct data quality issues at source
- Analyze systems and processes to find efficiencies and improve accuracy and timeliness of reporting
Benefits
- comprehensive health care coverage and emotional well-being support
- market-leading retirement
- generous paid time off and parental leave
- charitable giving employee match program
- educational assistance including student loan repayment, tuition reimbursement, and learning resources to develop your career
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Number of Employees
101-250 employees
