Senior Analytics Engineer, Product

This is a fully remote position, open to applicants in United States.

📋 Description

• Create engaging experiences for our customers. Collaborate within the Video product organization alongside product managers, designers, and engineers, utilizing data to influence and deliver features that athletes and their families will truly appreciate. You will be an integral part of the product team, rather than a separate reporting function.

• Enhance and expand our data infrastructure. Refine existing models and pipelines to ensure they are cleaner, more dependable, and reusable, while also incorporating new product, customer, and third-party signals that are currently absent, and maintaining software discipline (version control, review, testing) to foster trust in the data and answer previously unresolvable questions.

• Implement a scalable experimentation framework. Establish the data and analytical infrastructure for A/B testing, enabling the team to design, execute, and interpret experiments swiftly and consistently without needing to reconstruct the framework each time.

• Ensure accurate instrumentation from the outset. Collaborate with product and engineering teams on event tracking and data contracts to guarantee that important behaviors are captured correctly and thoroughly from the beginning, followed by developing tests and monitoring systems to maintain this accuracy.

• Empower products with real-time data APIs. Design and manage data endpoints that support live product features, from specifications through to production.

• Extract insights and influence decisions. Transform key metrics into actionable insights and recommendations that drive business outcomes, creating dashboards and interfaces that stakeholders rely on for informed decision-making.

• Create predictive and causal models. Develop models that influence business strategies, including a pLTV model for revenue forecasting, a propensity model to target discounts without undermining revenue, and causal-inference analyses to identify behaviors that enhance retention.

⛳️ Requirements

• Proficient in SQL with a strong capability to work with large analytical datasets, including complex joins, window functions, and performance optimization in a cloud warehouse (we utilize Snowflake).

• Strong instincts in data modeling with a proven record of creating clean, documented, and reusable transformation layers (SQLMesh, dbt, or similar tools).

• Proficient in production-level Python for modeling, orchestration, and analyses that SQL alone cannot address, including statistical methods necessary for developing LTV or propensity models and accurately assessing causation versus correlation.

• Experience in building data products that others rely on: APIs, pipelines, and dashboards, not merely ad-hoc queries.

• Stakeholder communication skills: you effectively translate business inquiries into universally accepted metrics and influence decisions with your creations.

• Familiar with experimentation and A/B testing sufficient to establish the measurement and analysis frameworks that tests rely on.

• Acquainted with AI-enhanced development tools (such as Claude, Codex) within a modern workflow, with a propensity for delivering quickly where speed is crucial and perfection hinders progress.

• **Bonus:** Experience in data modeling for analytical or operational use cases; familiarity with real-time or streaming data systems; foundational knowledge of ML engineering such as feature pipelines; background in sports, streaming, or B2C subscription sectors.

🏝️ Benefits

• Multiple medical insurance options available.

• Dental, vision, life, and disability insurance included.

• Employee Emergency Fund provided.

• Company equity (stock options) offered.

• Open PTO policy for work-life balance.

• 401K plan with company matching contributions.

• Hybrid and flexible work environment.