Head - Data Analytics

Key

• Strategy & Operating Model
• Define and execute the enterprise analytics strategy and roadmap aligned to OKRs/KPIs across business units.
• Establish the analytics operating model, delivery processes, and SLAs for self-serve BI and centralized analytics.
• Champion data literacy and evidence-based decision-making across the organization.
• Stakeholder Consulting & Business Impact
• Act as the analytics partner to business leaders; translate ambiguous business problems into analytical formulations and measurable hypotheses.
• Build executive-ready narratives: synthesize insights, trade-offs, and recommendations to influence strategic decisions.
• Define and track value realization from analytics initiatives (revenue lift, cost savings, risk reduction, CX improvements).
• Insight Products & BI
• Own the design and governance of KPI frameworks, executive dashboards, and automated reporting across Product, Growth/Marketing, Sales, Operations, Risk, and Finance.
  
• Drive standard definitions, metric catalogs, and data quality for trustworthy insights.
• Prioritize and deliver a backlog of insight products that scale with the business.
• Advanced Analytics & Experimentation
• Lead development of statistical analysis, forecasting, segmentation, propensity and LTV models, and causal inference frameworks for growth and retention.
• Institutionalize A/B testing and experimentation; ensure robust design, guardrails, and learnings at scale.
• Partner with Data Science on ML use cases; ensure business adoption and monitoring of models.
• Data Foundations & Governance (in partnership with Data Engineering)
• Influence data architecture for analytics: semantic layers, marts, and data contracts for reliable consumption.
• Drive data quality management, lineage visibility, and governance standards; ensure compliance with privacy and regulatory needs.
• Team Leadership
• Build and mentor a high-performing team of Analytics Managers, BI Developers, and Data Analysts.
• Set clear goals, career paths, and upskilling plans; foster a culture of curiosity, rigor, and outcomes.
• Manage vendor partnerships and external tooling where relevant.

Required

• 7 - 10 years of progressive experience in analytics, with at least 3 - 5 years in people management and leading multi-stakeholder analytics programs.
• Demonstrated impact leading analytics in at least two of the following domains: Product Analytics, Growth/Marketing Analytics, Risk/Credit Analytics, Revenue/Commercial Analytics, Customer/Operations Analytics.
• Proven track record of building executive dashboards, KPI frameworks, and running experimentation programs that drive measurable business outcomes.
• Experience collaborating with data engineering and data science teams to deliver scalable insight products and ML-powered decisioning.
• Bachelor's or Master's in a quantitative field (Engineering, Statistics, Mathematics, Economics, Computer Science) or equivalent experience.

Technical

• Strong SQL and data modeling for analytics; comfort with large-scale datasets.
• Proficiency in BI/visualization tools (e.g., Power BI, Tableau, Looker) and dashboard governance.
• Statistical analysis and experimentation: hypothesis testing, causal inference basics, time-series