Investment Data Operations Lead

London Source: WhatJobs

£120,000–£150,000

Investment Data Operations Lead - Director - Investment Management / Asset Management

Our client is a leading Asset Management company based in London and is seeking seeking a data expert to join a new Risk Data Operations team responsible for ensuring that all vendor and internal portfolio risk analytics used for risk management and portfolio construction across the organisation are delivered consistently, accurately and on a timely basis.

The team are the stewards of risk analytics data. 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 provide data expertise to portfolio and risk managers who use portfolio risk models and engineering teams which build production processes around them.

This is a lead role and will serve as a player/coach, responsible for individual deliverables and will mentor more junior members of the team, helping them gain the domain expertise necessary to root-cause daily issues effectively, work with internal and external data providers to resolve issues at source, answer investor questions, and develop automated systems for identifying data quality issues. The role requires some experience / knowledge or risk analytics data.

Specific duties and and experience required:

Proven experience with market risk models from leading vendors such as Barra, Axioma, Northfield, and Bloomberg.
Strong analytical capabilities with a demonstrated ability to comprehend large datasets and implement effective data quality controls.
Proactive and self-motivated approach, with the ability to work independently while providing oversight and mentorship to junior team members.
Understanding of financial data including security, company, portfolio, and index-level information, as well as pricing across equities, bonds, and derivatives.
Proficiency in SQL, Python, Snowflake, and/or Oracle, with hands-on experience in data quality frameworks and automation tools.
Bachelor’s degree or higher in a quantitative discipline such as mathematics, statistics, engineering, computer science, or finance.
Experience in global data operations or support roles within the financial industry, with a track record of delivering high-quality data solutions.
Exposure to anomaly detection methods, statistical tools, and best practices for managing data quality workflows.
Excellent communication skills, with experience collaborating across technical, investment, and senior leadership teams.
Demonstrated leadership in team environments, including mentoring junior associates and driving process improvements.
Experience working in complex data environments, with the technical and analytical infrastructure required to support them.
Ability to identify and resolve root-cause data quality issues, collaborating with internal teams and external data providers to correct issues at the source.
Skilled in developing automated processes to detect and resolve data errors, ensuring high-quality data for investment decision-making.
Experience in documenting key procedures and calculations and validating data for accuracy and completeness.
Domain expertise in investment management, with knowledge spanning risk management, portfolio management, trading, and investment operations.