Description
By joining Sedgwick, you'll be part of something truly meaningful. It's what our 33,000 colleagues do every day for people around the world who are facing the unexpected. We invite you to grow your career with us, experience our caring culture, and enjoy work-life balance. Here, there's no limit to what you can achieve.
As a Director of Product Management, Data Science, you will define and execute product strategy and outcomes for a portfolio of data science products, including predictive models, statistical and forecasting solutions, and advanced analytics capabilities. This role owns roadmap direction, investment prioritization, and delivery accountability, ensuring data science work moves beyond analysis and experimentation into scalable, production-ready solutions that deliver measurable business value.
Key Responsibilities:
- Set product vision and roadmap for a portfolio of data science products, aligning business priorities with data platform direction, architectural standards, and long-term scalability.
- Lead portfolio discovery and strategic planning to identify high-value opportunities for predictive modeling, forecasting, segmentation, and optimization.
- Ensure business problems are framed in ways data science can solve, with clear decision points, success measures, and an understanding of how model outputs will be used in operational workflows.
- Partner with senior business, technology, data science, and operations leaders to align scope, sequencing, and investment decisions.
- Establish outcomes that connect model performance to business results, and communicate product strategy, progress, risks, and architectural implications to executive stakeholders.
- Oversee delivery across product and data science teams, ensuring alignment between product strategy, model development, technical execution, and client outcomes.
- Set expectations for backlog quality and acceptance criteria across teams.
- Partner with Data Science, Data Engineering, and architecture leadership to manage dependencies, data pipelines, integrations, capacity planning, and delivery risks across the portfolio.
- Ensure a clear path from exploratory analysis and proof of concept to production.
- Own accountability for portfolio KPIs and contributions to Product Group and enterprise OKRs.
Requirements:
- Bachelor's degree in Statistics, Data Science, Mathematics, Computer Science, Economics, or a related quantitative field from an accredited college or university preferred.
- Ten (10) or more years of experience in product management or product strategy, including at least three (3) years managing data science, predictive analytics, or machine learning products.
- Demonstrated track record of taking predictive models or other data science solutions from concept through production deployment and measurable business impact.
- Expert knowledge of agile methodologies and product operating models.
- Strong working knowledge of the data science lifecycle.
- Solid grounding in statistical concepts.
- Fluency in model evaluation measures and the ability to translate model performance into business impact.
- Understanding of experimental design.
- Familiarity with common data science tools and languages such as Python, R, and SQL.
- Working knowledge of model governance, model risk management, and data privacy requirements in regulated industries.
Benefits:
- Sedgwick is an Equal Opportunity Employer and a Drug-Free Workplace.
- Newsweek Recognizes Sedgwick as America's Greatest Workplaces National Top Companies.
- Certified as a Great Place to Work.
- Fortune Best Workplaces in Financial Services & Insurance.