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BeviBevi

Product Data Scientist

The Product Data Scientist owns analytics for digital product experiences, measures flavor-launch impact, and builds a constrained flavor recommendation engine. The role requires 2–4 years of experience, strong GA4 and experimentation expertise, SQL and Python/R proficiency, and effective stakeholder communication.

About the job

Responsibilities

  • Own analytics for Bevi-proprietary digital experiences, including the UI and the Well; consult with Software on tracking structure and analyze performance to inform the product roadmap.
  • Own tracking and analytics for Bevi.co and Partner.co, including GA4 and tag management.
  • Recommend analytics tools for web properties alongside GA4/GTM, including session replay, self-serve data, testing, and heatmaps.
  • Measure the incremental impact of new flavors using A/B testing and non-traditional methods when clean experiments are not possible.
  • Build a flavor recommendation engine to identify the optimal flavor profile per machine or cluster, subject to constraints such as weekly maximum updates and required static options.
  • Translate data and analytics into clear insights and recommendations.
  • Build informative dashboards and drive adoption of product data.
  • Partner with data engineering and software teams on data quality, tagging, and instrumentation.

Requirements

  • 2–4 years of professional experience in product analytics, digital analytics, or data science.
  • Hands-on experience with GA4 and tag management, such as GTM, including tracking implementation and analysis.
  • Experience designing and analyzing experiments, including A/B testing and quasi-experimental methods such as pre/post analysis, difference-in-differences, and propensity score matching.
  • Strong SQL and Python or R skills for querying, modeling, and analysis.
  • Experience with data visualization tools such as Looker, Power BI, or Hex.
  • Ability to use AI tools in analytics, coding, and documentation workflows and make product data accessible to AI tools and people.
  • Proactive approach and ability to drive work to completion independently.
  • Excellent communication skills with the ability to translate complex findings into clear, actionable recommendations for non-technical stakeholders.

Compensation and Benefits

  • Annual salary range: $120,700–$149,100 USD.
  • Stock options for all employees.
  • Full-time employees are eligible for a Total Rewards plan, including health and medical benefits, flexible spending accounts, flexible paid time off, and more.
  • Medical, dental, and vision insurance, with 95% of premiums paid by the employer.
  • 401(k) with company match.
  • Flexible PTO, company holidays, and additional paid sick leave.
  • Fully paid parental leave for birth and non-birth parents.
  • Employer-paid disability and life insurance.
  • Wellness and fitness reimbursements.
  • Monthly cell phone and commuting stipends.
  • Onsite snacks, catered lunches, and other team events.

Skills

Ga4, Google Tag Manager, A/B Testing, SQL, Python, R, Looker, Power BI, Hex, Recommendation Systems, Machine Learning, Data Visualization, Product Analytics, Quasi-Experimental Methods, Dashboarding

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