Risk Analytics Manager

Responsibilities

• Lead, mentor, and manage a team of Risk Analysts, fostering a high-performance, collaborative, and innovative team culture.
• Dedicate approximately 20% of time to individual contributor (IC) work, actively contributing to core analytical projects and maintaining hands-on technical proficiency.
• Define, prioritize, and oversee the Risk Analytics roadmap, ensuring alignment with overall Risk Department and company objectives.
• Set standards for terms, metrics, data visualization, reporting, and automation across the risk department, ensuring accuracy, consistency, and timely delivery.
• Conduct performance reviews, provide constructive feedback, and support the professional development of team members.
• Serve as the primary point of contact for stakeholders on Risk Analytics deliverables, translating complex analytical findings into clear, actionable business recommendations for executive leadership and cross-functional teams.
• Drive the strategic analysis of transaction and customer data to proactively identify emerging fraud and credit risk trends and propose innovative control strategies.
• Collaborate closely with coworkers in the Risk Data Science, Risk, and Ops teams.
• Build and optimize queries, determine best sources and approach for data and insights.
• Aid in determining, scoping, and creating data products and data governance related to the Risk Data Science team.
• Engage on both strategic ad-hoc requests and projects, conducting independent research to propose rules and strategies to help mitigate risks across all products.
• Proactively stay updated on industry trends, best practices, and regulatory requirements related to risk management and fraud prevention.

Requirements

• Must have a high level of proficiency in using SQL for data analysis.
• Must have experience managing direct reports.
• Demonstrated ability to be a hands-on leader, committed to coaching and developing junior analysts in SQL querying, rigorous data analysis techniques, effective presentation skills, and clear communication of complex findings.
• Experience with building data visualizations and dashboards (Qlik preferred, or Tableau, Looker, Power BI, etc.).
• Strong analytical skills with the ability to work with large datasets to identify patterns, trends, and anomalies in time series data is preferred.
• BS or advanced degree in STEM or related field is preferred.
• 5+ years’ experience in data analysis or related roles, preferably in the Fintech or Payments industry.
• Familiarity with card payments or banking/finance industry, including knowledge of transactional payment data analysis, experience with card association Risk and Dispute process/procedures is highly preferred but not mandatory for this role.
• Must be able to clearly communicate with technical and non-technical audiences.
• Must be a team player and regularly collaborate with team members to enhance the culture of helpfulness and high impact.