Remote Director of Data Science Product Strategy

Sedgwick; Tampa (FL); Remote; USD 150,000 - 230,000; Full time

Job summary

Sedgwick is seeking a Director of Product Management, Data Science to define and execute product strategy for a portfolio of data science products, including predictive models and analytics capabilities. You will own roadmaps, prioritization, and delivery accountability, leading product managers and partnering with data science and engineering leaders.

You will establish outcomes that tie model performance to business value, govern lifecycle, and ensure production-ready solutions.

Qualifications

• Bachelor's degree in Statistics, Data Science, Mathematics, Computer Science, Economics or related field preferred.
• Advanced degree preferred.
• Ten or more years in product management or strategy; at least 3 years in data science or ML products.
• Proven track record taking models from concept to production and measurable business impact.
• Experience with agile development is highly preferred.

Responsibilities

• Set product vision and multi-year roadmap for data science product portfolio.
• Lead portfolio discovery and strategic planning for predictive modeling and analytics.
• Frame business problems for data science with clear success measures and usage in workflows.
• Partner with senior leaders to align scope, sequencing, and investments.
• Own portfolio KPIs and contribute to OKRs including model accuracy, adoption, and value.

Skills

Agile methodologies

Data science lifecycle

Statistical concepts

Model evaluation metrics

Leadership

Communication to executives

Education

Bachelor's degree in Statistics, Data Science, Mathematics, Computer Science, Economics

Advanced degree preferred

Tools

Python

R

SQL

Job description

Sedgwick is seeking a Director of Product Management, Data Science to define and execute product strategy for a portfolio of data science products, including predictive models and analytics capabilities. You will own roadmaps, prioritization, and delivery accountability, leading product managers and partnering with data science and engineering leaders.

You will establish outcomes that tie model performance to business value, govern lifecycle, and ensure production-ready solutions.