The role:

As a Risk Data Analytics Manager in our Risk Management function, you will play a crucial role in driving data-driven decision making. You'll collaborate closely with senior leadership to understand their needs, develop innovative data visualizations, and provide valuable insights to support risk oversight.

What you’ll do:

• Partner with senior leaders in the Independent Risk Management function to provide consultancy and translate the business needs to design and develop tools, techniques, metrics, and dashboards for insights and data visualization.
• Translate business requirements into impactful dashboards, metrics, and visualizations to support risk identification, measurement, and monitoring.
• Combine both internal and external data to conduct analysis to provide meaningful insights on risk management strategies and the macroeconomic environment.
• Conduct quantitative analyses using statistical methods, econometric analysis, financial modeling, and other risk management techniques.
• Prepare and analyze risk reports for senior management and regulatory bodies.
• Design, develop, and maintain datasets and pipelines to support risk analytics, including data ingestion, transformation, and quality assurance.
• Implement and maintain data quality standards and controls to ensure data accuracy, consistency, and completeness.
• Leverage industry leading technologies and integrate new data attributes uncover valuable insights and solve complex business problems.
• Continuously explore new technologies and techniques to improve our analytics capabilities and deliver greater value.

What you’ll need:

• Bachelor’s degree in Computer Science, Engineering, Statistics, Econometrics or a quantitative field required. Master’s or Ph.D. degree preferred.
• 6+ years of impactful experience in the financial services industry, with significant depth in risk management (e.g. market risk, credit risk, liquidity risk, ops risk).
• Ability to translate business needs into impactful and appealing interactive dashboards, Streamlit applications, and reports.
• Strong quantitative skills, including proficiency in statistical analysis, econometrics, stress testing, decision science, and other risk measurement techniques.
• Deep hands-on experience with core technologies such as Airflow, dbt, git, docker,, Tableau, Streamlit, AWS, Snowflake, and Python.
• Strong SQL skills with demonstrable competencies in designing well-architected data models and optimizing query performance.
• Proven experience building analytics solutions leveraging Git workflows, modularized coding practices, API calls, and web based solutions.
• The ability to analyze complex data, identify patterns, and develop solutions to address business challenges.

Nice to have:

• Notable financial designation(s) such as CFA or FRM