Commercial Product Manager Lead for Risk Analytics and Data Quality

FIS•Atlanta, GA

About The Position

FIS is seeking a senior, hands-on leader to drive delivery across Risk Analytics and Data Quality initiatives. In this role, you will lead a hybrid team (domestic and offshore) and partner closely with stakeholders to plan, execute, and continuously improve analytics and data-quality solutions supporting risk and compliance priorities. What you will do: Lead day-to-day delivery for Risk Analytics and Data Quality workstreams, balancing people leadership with hands-on analytical execution. Supervise, coach, and develop a team of domestic and offshore data professionals; coordinate workload, priorities, and delivery commitments. Partner with stakeholder teams across Risk Analytics and Enterprise Data Management to scope work, set expectations, and deliver results. Own project planning, execution, and reporting for assigned initiatives; manage resources and risks to meet timelines and quality expectations. Establish and maintain standards for documentation, reproducibility, scalability, and model/data governance. Risk Analytics responsibilities Plan, develop, and deliver analytical models including classification and predictive models, scoring and rules-based models, and other advanced analytics techniques (machine learning and artificial intelligence). Perform problem framing and analysis; lead data collection, integration, exploration, and preparation to support modeling objectives. Guide model implementation in partnership with technology and business teams, ensuring solutions are production-ready and measurable. Support analytics needs across Fraud Prevention, Anti-Money Laundering (AML), Compliance, Credit Risk, Market Risk, Operational Risk, and Finance. Apply appropriate methodology across the model lifecycle, including tracking, documentation, reproducibility, scalability, monitoring, and actionable insights. Data Quality responsibilities Develop and oversee analytical controls and reporting to identify and track data-flow issues across systems and data sources. Define and monitor critical data elements; detect unexpected values and potential quality defects. Drive issue triage and resolution by partnering with stakeholders; track remediation through to closure. Team & working style You will lead a high-performing, globally distributed team supporting Risk Analytics and Data Quality initiatives. Success in this role requires strong collaboration across time zones and the ability to translate stakeholder needs into clear, executable plans.

Requirements

10+ years of experience in banking and analytics, including senior-level stakeholder engagement and delivery ownership.
Graduate degree in Statistics, Data Science, Applied Economics, Machine Learning, or a related field (or equivalent experience).
Strong foundation in statistics, data science, and modern analytical techniques, including machine learning and AI concepts.
Proficiency with analytical programming and data tools such as Python, SAS, R, and SQL.
Experience leading teams and delivering work through clear planning, prioritization, and execution.
Excellent written and verbal communication skills, with the ability to explain complex analytical topics to technical and non-technical audiences.
Proficiency with Windows productivity tools (e.g., Microsoft Office).

Nice To Haves

Working knowledge of Power BI.
Experience with Monday.com or a similar project management tool.

Responsibilities

Lead day-to-day delivery for Risk Analytics and Data Quality workstreams, balancing people leadership with hands-on analytical execution.
Supervise, coach, and develop a team of domestic and offshore data professionals; coordinate workload, priorities, and delivery commitments.
Partner with stakeholder teams across Risk Analytics and Enterprise Data Management to scope work, set expectations, and deliver results.
Own project planning, execution, and reporting for assigned initiatives; manage resources and risks to meet timelines and quality expectations.
Establish and maintain standards for documentation, reproducibility, scalability, and model/data governance.
Plan, develop, and deliver analytical models including classification and predictive models, scoring and rules-based models, and other advanced analytics techniques (machine learning and artificial intelligence).
Perform problem framing and analysis; lead data collection, integration, exploration, and preparation to support modeling objectives.
Guide model implementation in partnership with technology and business teams, ensuring solutions are production-ready and measurable.
Support analytics needs across Fraud Prevention, Anti-Money Laundering (AML), Compliance, Credit Risk, Market Risk, Operational Risk, and Finance.
Apply appropriate methodology across the model lifecycle, including tracking, documentation, reproducibility, scalability, monitoring, and actionable insights.
Develop and oversee analytical controls and reporting to identify and track data-flow issues across systems and data sources.
Define and monitor critical data elements; detect unexpected values and potential quality defects.
Drive issue triage and resolution by partnering with stakeholders; track remediation through to closure.