Digital Analytics Manager

This is a remote position.

We are seeking a Digital Analytics Manager to lead the strategy, design, and implementation of a comprehensive measurement framework for all our AI products and applications. This role will be instrumental in defining success metrics, enabling data-driven decision-making, and ensuring consistent, actionable analytics across our AI initiatives. You will work closely with product, engineering, data science, and business teams to establish best-in-class analytics practices that track performance, drive insights, and support continuous improvement.

Key Responsibilities:

• Establish a Unified Measurement Framework: Design and implement a scalable analytics strategy to track usage, performance, engagement, and business impact of all AI products.
  
• Define and Operationalize Metrics: Partner with cross-functional teams to identify key performance indicators (KPIs), success metrics, and diagnostic measures for AI features and applications.
  
• Lead Instrumentation Strategy: Guide engineering teams on data instrumentation and ensure proper tagging, tracking, and data pipeline setup across platforms.
  
• Drive Insightful Reporting: Build dashboards and reports that provide clear visibility into product performance, user behavior, and model efficacy to inform roadmap decisions.
  
• Advocate for Data-Driven Culture: Promote the use of metrics and experimentation in product development; help teams interpret analytics and take data-informed actions.
  
• Mentor and Lead: Build and manage a small team of analysts (as needed), and foster strong analytics capabilities within the broader organization.
  

Qualifications:

• 7+ years of experience in digital/product analytics, with at least 2+ years in a leadership or strategic role.
  
• Experience defining analytics for AI/ML products or data-driven applications.
  
• Strong understanding of product analytics tools (e.g., Amplitude, Mixpanel, Google Analytics, Adobe Analytics) and data platforms (e.g., BigQuery, Snowflake).
  
• Skilled in SQL and data manipulation; familiarity with Python or R is a plus.
  
• Experience with A/B testing, cohort analysis, funnel metrics, and predictive analytics.
  
• Proven ability to collaborate with technical and non-technical stakeholders to drive decisions through data.
  
• Strong communication, storytelling, and visualization skills.
  

Originally posted on Himalayas

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