Director, Data Analytics

Responsibilities

• Lead the analytics function across the organization, ensuring consistency in methodologies, toolsets, and quality standards across all embedded teams.
• Work closely with Department Leads to align analytics roadmaps with broader business goals and P&L objectives.
• Establish and monitor the adoption of standardized processes for experimentation, data modeling, and reporting.
• Act as an expert to structure and guide deep dive exploratory, root-cause analyses and business cases.
• Get hands-on with data to solve the company's most complex or ambiguous problems.
• Participate in formal reviews for RFCs, experimental designs, and learning briefs; provide oversight on success metrics and interpretation of complex test results.
• Manage the performance, career tracks, and professional growth of Analytics Managers and Leads.
• Manage team bandwidth and prioritize high-impact initiatives.
• Step in to lead work streams directly if needed.
• Develop and expand the analytics organization to support business growth.
• Drive the adoption of a data-driven culture by delivering insights to executive leadership.
• Collaborate closely with peers across engineering, analytics engineering, and data science organizations.

Requirements

• 10+ years of experience in data analytics, including 5+ years in the D2C domain.
• 5+ years of leadership experience managing managers and overseeing cross-functional or embedded analytics structures.
• Expert proficiency in SQL and Python.
• Expertise in the design, interpretation, and monitoring of randomized controlled trials (A/B/n testing) and statistical inference.
• Skilled in developing and interpreting complex, advanced experimental frameworks.
• Proven track record of using data to drive strategy and influence at all levels.
• Ability to translate complex data into compelling narratives and actionable insights.
• Experience designing and implementing dashboards.
• Experience with dimensional modeling using Kimball methodologies.
• Root-cause analysis skills to turn ambiguous data into business opportunities.
• Experience building scalable analytics infrastructure.
• Advanced degree in a quantitative field (Statistics, Economics, Computer Science, etc.) or equivalent practical experience.

Nice-to-Haves

• Direct experience in the D2C Fintech domain.
• Experience managing distributed or hybrid teams across time zones.
• Expertise in data transformation and modeling.