Product Analytics Senior Manager (IC)

Position Summary

The Product Analytics Senior Manager is an individual contributor role within the Product Management team. This role is responsible for the product analytics strategy to inform and influence product decisions. The Senior Manager will build scalable, self-service reporting, design and analyze experiments, map and optimize product funnels, and translate data into actionable insights. Over time, the role will also leverage AI/ML-driven analytics to surface deeper insights and predictive recommendations.

Responsibilities

• Self-Serve Dashboards & Reporting
  • Design and maintain Looker dashboards that give product, marketing, and operations leaders direct access to the metrics that matter most.
  • Define a single source of truth for core KPIs (enrollment conversion, retention save rates, average handle time, customer lifetime value), working across Snowflake and Salesforce data sources.
  • Partner with Engineering and Data Engineering to ensure clean, well-documented data models underpin all reporting.
• Experimentation & A/B Testing
  • Build and manage the experimentation framework from the ground up: test design, instrumentation, statistical analysis, and readout.
  • Advise product managers on experiment design, sample sizing, and how to distinguish signal from noise.
  • Maintain a test-and-learn log that connects experiment outcomes to roadmap decisions.
• Funnel & Conversion Analytics
  • Own end-to-end funnel analysis from awareness through enrollment and renewal, using Google Analytics, Contact Lens call data, and Salesforce pipeline data.
  • Surface friction points and drop-off patterns with enough specificity to drive immediate product and operational action.
  • Partner with the Contact Center and Marketing teams to instrument new touchpoints and improve measurement coverage.
• AI & Emerging Analytics Initiatives
  • Support the company’s Agentic AI roadmap by contributing analytical rigor to AI performance measurement (tracking model outcomes, agent effectiveness, and downstream business impact) via Amazon Bedrock and Contact Lens.
  • Identify opportunities to apply ML techniques (propensity modeling, churn prediction, next-best-action) where analytics naturally evolves into intelligence.

Qualifications

• 5+ years of experience in product analytics, data analytics, or a closely related function.
• Advanced SQL expertise with the ability to independently write complex queries and model data in Snowflake or a comparable cloud data warehouse.
• Hands-on experience building Looker (LookML) dashboards or similar BI tools.
• Strong understanding of experimental design and statistical inference.
• Experience working with digital analytics platforms such as Google Analytics and connecting behavioral data to business outcomes.
• Ability to translate ambiguous business questions into structured analytical approaches and clearly communicate insights to non-technical stakeholders.
• Comfortable operating independently with a high level of ownership and accountability.

Preferred Qualifications

• Experience with AWS analytics services, including Amazon Connect Contact Lens.
• Familiarity with Salesforce Service Cloud and CRM data structures.
• Exposure to machine learning workflows (e.g., Python, scikit‑learn, SageMaker, or Bedrock).
• Background in subscription‑based, insurance, warranty, home services, or contact‑center‑driven businesses.

Computer Skills

• Snowflake — cloud data warehouse
• Looker — BI and self-serve dashboards
• Google Analytics — web and digital behavioral data
• Amazon Connect & Contact Lens — call recording, transcription, and sentiment (AWS)
• Amazon Bedrock — generative AI / LLM infrastructure
• Salesforce Service Cloud — CRM and operational data

Education

• Bachelor’s degree in Engineering, Business, Analytics, or equivalent practical experience.

Competencies

• Problem Solving - Uses rigorous logic and methods to solve difficult problems with effective solutions; probes all fruitful sources for answers; can see hidden problems; is excellent at honest analysis; looks beyond the obvious and doesn't stop at the first answers.
• Strategic Agility - Sees ahead clearly; can anticipate future consequences and trends accurately; has broad knowledge and perspective; is future oriented; can articulate credible pictures and visions of possibilities and likelihoods; can create competitive and breakthrough strategies and plans.
• Action Orientated - Enjoys working hard; is action oriented and full of energy for the things that he/she sees as challenging; not fearful of acting with a minimum of planning; seizes more opportunities than others.
• Functional / Technical Skills – Has the functional and technical knowledge and skills to do the job at a high level of accomplishment.
• Organizational Agility - Knowledgeable about how organizations work; knows how to get things done both through formal channels and the informal network; understands the origin and reasoning behind key policies, practices, and procedures; understands the cultures of organizations.