Analytics Manager

Responsibilities

Analytics, Strategy & Business Impact

• Own analytics strategy and decision support across business domains.
• Translate ambiguous business questions into analytical frameworks, recommendations, and action plans.
• Conduct deep-dive analyses of customer behavior, marketplace dynamics, product performance, growth opportunities, and business performance.
• Partner with business leaders to identify opportunities, define success metrics, measure impact, and guide tradeoffs.
• Design and evaluate experiments for product, marketing, and operational decisions.

Machine Learning & AI

• Develop predictive and statistical models that improve business outcomes.
• Identify opportunities to apply machine learning and AI to customer experiences, internal workflows, prioritization, and decision support.
• Partner with Product, Engineering, and business teams to evaluate, prototype, and operationalize AI-driven solutions.
• Apply machine learning, statistical modeling, automation, and generative AI to practical business use cases.
• Help shape responsible use of analytics and AI through practical use cases, measurable value, and trusted outputs.

Reporting, Data Quality & Enablement

• Build and maintain dashboards, recurring reporting, and self-service assets.
• Define and maintain trusted business metrics, KPI frameworks, and measurement standards.
• Validate data quality, investigate anomalies, reconcile discrepancies, and surface risks in analytical outputs.
• Partner with data and engineering teams to improve data reliability, usability, and scalability.
• Automate repetitive analytical workflows and improve team processes, templates, QA checks, and stakeholder workflows.

Stakeholder Partnership & Leadership

• Act as a trusted analytics partner and primary point of contact for assigned stakeholder groups.
• Lead intake and prioritization for analytical work by clarifying goals, scoping projects, setting expectations, and communicating progress.
• Tell clear, compelling stories with data and influence decisions through evidence-based recommendations.
• Mentor analysts and stakeholders informally through code reviews, analytical approaches, measurement design, and best practices.
• Operate independently in ambiguous, fast-moving environments with ownership and accountability for outcomes.

Requirements

• 5–7 years of experience in analytics, data science, quantitative strategy, or a related field.
• Bachelor’s degree.
• Advanced SQL skills and ability to move independently from raw data to actionable recommendations.
• Strong Python experience for statistical analysis, machine learning, and automation.
• Experience designing and analyzing experiments, including A/B testing or causal measurement.
• Experience building predictive models or applying machine learning to real-world business problems.
• Experience with Snowflake and Looker.
• Strong communication skills and ability to translate complex analytical concepts into clear business recommendations.
• Ability to influence decisions through data and build strong cross-functional partnerships.
• Comfort operating in ambiguity with significant ownership, autonomy, and accountability.

Nice-to-Haves

• Experience deploying, operationalizing, or monitoring machine learning models in a business environment.
• Experience with customer lifecycle, marketplace, fintech, investment, product, or growth analytics.
• Experience using generative AI or LLM-based tools for analytical workflows or practical business solutions.
• Familiarity with product analytics, marketing measurement, experimentation platforms, or event instrumentation.

Compensation

• San Francisco annual salary range: $120,000–$150,000, plus annual bonus.
• Final offers may vary based on geography, experience, expertise, bonus, and other factors.