Data Product Manager

Quick Facts

• Role: Data Product Manager (Consumer and Commercial data products)

• Focus: Delivery of data and analytics through product roadmaps, agile execution, and business adoption

• Core areas: Demand & design, delivery accountability, go-to-market & adoption

Description

You will lead data product delivery for consumer and commercial data products by defining and executing data roadmaps, capturing business/data requirements, and translating them to technical teams. You will run agile cross-functional PODs to deliver end-to-end solutions and serve as the voice of Data, Analytics, and AI to leadership. You will also drive adoption so outputs remain aligned to business use cases and generate actionable value.

Responsibilities

• Define the product/data roadmap and capture comprehensive requirements.

• Design solutions with technical teams to optimize end-to-end efficiency.

• Author technical data requirements and delivery lifecycle documents.

• Manage delivery against technical milestone targets.

• Ensure teams understand the business “why.”

• Write and steward user stories/requirements in Azure DevOps with Data Science, Data Engineering, Stewardship, Governance, and BI/Visualization teams.

• Manage output and development of other Data Product Managers.

• Manage business customer expectations and eliminate disconnects.

• Collaboratively manage reporting on D&Ai execution against key programs.

• Ensure outputs meet business requirements and translate analytics solutions into actionable business value.

• Collaborate with business and transformation teams to embed solutions and overcome implementation difficulties.

• Manage stakeholders effectively at all organizational levels.

• Foster a collaborative POD culture.

Requirements

• Bachelor’s degree required.

• 8 years of data product management in business-facing functions with strong agile and product lifecycle discipline.

• 3+ years leading/building advanced analytics and big data solutions or building enterprise SaaS.

• Deep understanding of machine-learning fundamentals (training vs predicting, performance measurement, overfit) and techniques such as random forests or neural networks.

• Familiarity with machine-learning technologies and tools, including big data stack and Python.

• Knowledge of data architecture, modeling, and engineering concepts; familiarity with Azure is a plus.

• Familiarity with data governance and stewardship principles and tools.

• Persuasive communication skills for both technical and business audiences.

• Ability to drive business-oriented and innovative solutions using data science, feature engineering, and machine learning.

• Strong initiative and ability to pursue growth opportunities.

• Experience presenting to C-Suite leadership.

• Excellent leadership and people management skills, including developing teams under time pressure.

Benefits

• Expected compensation range: $110,700–$185,250; actual starting salary depends on skills, experience, and education.

• Performance bonus: 12% of annual salary (subject to eligibility), paid annually.

• Paid time off subject to eligibility, including paid parental leave, vacation, sick, and bereavement.

• Comprehensive benefits package (subject to elections/eligibility): Medical, Dental, Vision, Disability, Health and Dependent Care Reimbursement Accounts, EAP, Accident/Group Legal/Life insurance, and Defined Contribution Retirement Plan.