Director of Product Management, Data Science

This is a fully remote position, open to applicants in Alabama, +19 more states.

📋 Description

• Develop and implement product strategy and outcomes for a suite of data science products

• Take ownership of roadmap direction, investment prioritization, and accountability for delivery

• Lead Product Managers while collaborating with leadership in Data Science, Data Engineering, and Architecture

• Articulate product vision and create a multi-year roadmap

• Drive portfolio discovery and strategic planning for predictive modeling, forecasting, segmentation, and optimization initiatives

• Formulate business challenges for data science with clear decision points and measures of success

• Align scope, sequencing, investment decisions, constraints, data dependencies, and model limitations with senior stakeholders

• Communicate product strategy, updates, risks, and architectural implications to executive stakeholders

• Oversee product and data science team deliveries

• Establish backlog quality and acceptance criteria, including model performance, validation, interpretability, and data requirements

• Manage dependencies, data pipelines, integrations, capacity planning, and delivery risks

• Create a pathway from exploratory analysis and proof of concept to production

• Own portfolio KPIs and contributions to Product Group and enterprise OKRs

• Maintain oversight of business processes, data sources, systems, and platform dependencies

• Collaborate with data governance, privacy, legal, compliance, and model risk teams

• Evaluate and authorize significant product, model, process, and system modifications

• Address priority, dependency, and delivery conflicts as a senior escalation point

• Manage the entire product and model lifecycle, including release readiness, monitoring, recalibration, retirement, and continuous improvement

• Foster data literacy among business stakeholders

• Stay updated on advancements in data science methods and practices

• Perform additional duties as assigned

• Travel as necessary

⛳️ Requirements

• Bachelor's degree in Statistics, Data Science, Mathematics, Computer Science, Economics, or a related quantitative field from an accredited institution is preferred

• An advanced degree is preferred

• A minimum of ten (10) years of experience in product management or product strategy, with at least three (3) years managing data science, predictive analytics, or machine learning products is required

• Proven track record of guiding predictive models or other data science solutions from concept to production deployment with measurable business impact is required

• Experience with agile development is strongly preferred

• Experience in claims, insurance, healthcare, financial services, or other regulated sectors is preferred

• Expert understanding of agile methodologies and product operating models, including scaling delivery across multiple teams and products

• Strong knowledge of the data science lifecycle, encompassing problem framing, data preparation, feature development, model development, validation, deployment, monitoring, and recalibration

• Solid foundation in statistical concepts, including regression, classification, forecasting, sampling, and statistical significance

• Proficiency in model evaluation metrics, such as precision, recall, AUC, calibration, and error rates

• Comprehension of experimental design, including A/B testing, control groups, and pilot design

• Familiarity with Python, R, and SQL

• Working knowledge of model governance, model risk management, and data privacy regulations in regulated industries

• Ability to convert business and portfolio strategies into product vision, roadmaps, and execution standards

• Strong portfolio-level judgment to balance investment, capacity, risk, technical health, and business outcomes

• Advanced skills in leading complex discussions with senior technical, data science, business, and executive stakeholders

• Proven ability to lead teams, including mentoring Product Managers, establishing expectations, and building high-performing teams

• Travel as necessary

🏝️ Benefits

• Work-life balance

• Consideration for reasonable accommodations

• Equal Opportunity Employer

• Drug-Free Workplace