Drive Delivery Performance

• Own a prioritized, outcome-oriented roadmap aligned to the highest-value business decisions
• Serve as the primary escalation point for blockers, cross-team dependencies, and resourcing constraints
• Monitor team output quality and proactively resolve systemic delivery issues before they affect product outcomes

Lead Cross-Functionally

• Build trusted working relationships with Engineering, Customer Success, Marketing, Sales, and Operations
• Position the data team as a strategic partner — not just a delivery function
• Represent the team at senior leadership levels and contribute a data and evidence-based perspective to the broadest product conversations

Champion Governance and Data Culture

• Establish and maintain standards for data quality, research methodology, and analytical integrity
• Develop guidelines for data privacy, ethical data use, and responsible research practices
• Drive a culture of continuous improvement in how the team gathers, analyzes, and translates data into product decisions

Head of Data Products Qualifications

• A bachelor's degree in a relevant field (data science, statistics, computer science, product management, social science, or equivalent) — or an equivalent combination of education and experience; at least 7 years of progressive experience in data, analytics, or product management; and at least 3 years leading a multi-function or cross-disciplinary team
• Demonstrated ability to effectively lead, with a track record of building high-performing, cohesive teams across data, analytics, and research disciplines
• Broad expertise across data product management, product analytics, and both qualitative and quantitative research methods — enabling you to set direction, evaluate quality, and integrate outputs across a multi-disciplinary team into a single, coherent product data strategy
• Outstanding data storytelling skills — the ability to translate complex findings into clear, compelling narratives for executive and non-technical audiences alike
• Strong command of data governance principles, including data quality standards, shared definitions, research ethics, and responsible data use
• Familiarity with product analytics tooling and data visualization platforms (e.g., Sigma, Tableau, Looker, or equivalent)
• Proven ability to manage competing priorities across concurrent workstreams without losing rigor, care, or momentum
• Deep collaborative instincts — experienced building effective partnerships across Engineering, Product, Customer Success, and business operations
• Experience working with customers and end-users to gather product requirements and define market needs

Originally posted on Himalayas