Senior Associate, Data Analytics and Risk Reduction

Responsibilities

• Develop and execute repeatable data-driven analyses to provide visibility into the operational risk landscape, identify risk reduction opportunities and support prioritization of risk reduction initiatives.
• Analyze large and complex datasets to identify risk trends, emerging patterns, process breakdowns, and systemic control gaps.
• Perform root cause analysis to understand underlying drivers of operational risk and recommend sustainable process improvements.
• Collaborate with Engineering, Product, Technology Risk, and Control Management teams to validate findings and develop practical, data-informed solutions.
• Measure and report on the effectiveness of implemented risk reduction initiatives using quantitative and qualitative performance metrics.
• Support special projects that evaluate emerging risks, ways of working, and operational process effectiveness.
• Communicate analytical findings through presentations, visualizations, and data storytelling that influence decision-making.
• Continuously identify opportunities to automate data collection, reporting, and monitoring to improve efficiency and scalability.

Qualifications

• 2+ years of experience in risk data analytics, operational risk, technology risk, process improvement, business intelligence, or related analytical functions.
• Experience analyzing complex datasets to identify trends, anomalies, root causes, and improvement opportunities.
• Strong analytical and problem-solving skills with the ability to convert data into actionable business insights.
• Strong project management, organizational, and stakeholder management skills with the ability to manage multiple concurrent initiatives.
• Excellent written and verbal communication skills.
• Ability to work independently while collaborating effectively across cross-functional teams.

Preferred Qualifications

• Bachelor's degree in Risk Management, Data Analytics, Statistics, Computer Science, Business Analytics, Finance, or related discipline.
• Experience supporting Digital Product, Software Engineering, Platform Engineering, or Technology organizations.
• Experience with operational risk management, process governance, technology controls, or software development lifecycle (SDLC) processes.
• Experience performing root cause analysis and translating findings into measurable process improvements.
• Experience building automated dashboards and visualizations using tools such as Tableau, Power BI, or similar business intelligence platforms.
• Experience querying and analyzing data using SQL and working with large, structured datasets.
• Experience using Python, R, or similar analytical programming languages for data analysis and automation.
• Familiarity with Agile delivery methodologies, DevSecOps practices, cloud technologies, or software engineering metrics.
• Knowledge of operational risk frameworks, Key Risk Indicators (KRIs), and control concepts.