Tala

Senior Product Analyst

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Job Description

The Senior Product Analyst is a strategic partner to Product, Engineering, and Design, responsible for shaping product direction through rigorous analysis, strong product intuition, and deep ownership of metrics, instrumentation, and experimentation. This role combines analytical depth with product thinking, enabling teams to understand user behavior, validate hypotheses, identify growth opportunities, and make high-quality decisions at speed. The Senior Product Analyst operates autonomously, leads analytical strategy for their product area, and ensures that the product team has a robust, batteries-included analytical foundation.



What You'll Do

Product Strategy and High-Context Insight

  • Partner with Product Managers to influence roadmap priorities through structured problem framing and opportunity sizing.

  • Drive end-to-end analytical discovery: define questions, shape hypotheses, perform root-cause analysis, and identify second-order effects.

  • Produce high-context, narrative-driven analysis that shapes product decisions—not just dashboards or metrics reporting.

  • Identify long-term analytical needs and proactively set the direction for how the product should be measured.

  • Metrics Architecture and Observability
  • Own the metric hierarchy for the product domain (north-star, input metrics, counter-metrics, diagnostic metrics).

  • Design tracking plans and instrumentation schemas; work with engineering to ensure correct implementation.

  • Implement automated alerting and monitoring to surface health issues, funnel breaks, outliers, and behavior shifts in real time.

  • Experimentation and Causal Inference
  • Lead the design, execution, and interpretation of experiments (A/B tests, multivariate tests, staggered rollouts).

  • Select and apply appropriate statistical techniques (frequentist/Bayesian, CUPED, time-series methods).

  • Evaluate experiment readiness, calculate required sample sizes, and estimate expected effects.

  • Translate experiment outcomes into clear recommendations for product and business stakeholders.

  • Analytical Leadership and Collaboration
  • Mentor and support junior analysts; set standards for analytical depth, clarity, and rigor.

  • Act as the analytical owner in cross-functional initiatives, ensuring alignment on metrics and success criteria.

  • Influence how PMs and engineers adopt analytical best practices, instrumentation, and metric stewardship.

  • Communicate trade-offs, risks, and insights to both technical and non-technical audiences with precision.

  • Ownership of Analytical Assets
  • Partner with Analytics Engineering to ensure models, marts, and pipelines meet quality standards and SLAs.

  • Ensure the product area has a batteries-included analytical environment—well-documented, reliable, and easy to use.

  • Maintain data lineage, definitions, and documentation to minimize ambiguity and reduce analytical debt.


  • What You'll Need

    Experience

  • 4-6 years in product analytics, data science, or growth analytics with extensive product-team experience.
  • Proven track record influencing product roadmaps with evidence-based insights.

  • Experience in high-velocity experimentation environments (consumer apps, fintech, SaaS, marketplaces).

  • Technical Skills
  • Expert SQL; fluency with Snowflake or equivalent cloud data warehouses.

  • Strong experimental design and statistical analysis skills.

  • Familiarity with event-based instrumentation and telemetry platforms.

  • Competence with data visualization tools and dashboards (Looker, Metabase, etc.).

  • Analytical and Product Skills
  • Strong product intuition; ability to identify friction, opportunity, and causal drivers in user behavior.

  • Ability to articulate ambiguous or complex insights through structured narratives.

  • Experience diving into systems, logs, metrics, and data models.

  • Ability to operate autonomously and drive analytical strategy for a product domain.

  • Mindset
  • Relentless ownership and high standards.

  • Customer-obsessed and curious about system behavior.

  • Comfortable making decisions under ambiguity and imperfect data.

  • Proactive, not reactive: anticipates analytical needs before they surface.