Product Data Analyst II
Analyzes product and customer data to develop metrics, evaluate features, inform pricing and monetization, and communicate actionable insights across the business. Requires 2+ years in an analytical role, advanced SQL, and experience with product analytics or data science.
About the job
Responsibilities
- Partner with business stakeholders to understand products and customers.
- Communicate analytical insights and recommendations to non-technical audiences across the organization.
- Collaborate with product owners and finance partners to evaluate new features, enhancements, and projects.
- Create customer profiles and develop metrics supporting pricing and monetization strategies.
- Develop AI context and evaluations that enable stakeholders to self-serve data models.
- Work with engineers to develop company-wide data sources and core metrics.
- Promote experimentation and a data-driven culture.
Requirements
- 2+ years of experience in a highly analytical role, including at least 1 year in product analytics or data science.
- Advanced SQL proficiency.
- Understanding of data warehouse principles and data modeling.
- Strong analytical, problem-solving, prioritization, written communication, and verbal communication skills.
- Ability to translate complex analyses into actionable insights and communicate business impact to non-technical audiences.
- Demonstrated ability to work independently and drive projects to completion.
Nice to Have
- Experience with dbt.
Compensation and Benefits
- Base salary range: $115,000–$135,000 USD.
- Competitive cash and equity compensation.
- Learning and development allowance.
- Medical, dental, and vision coverage.
- Up to $25,000 reimbursement for fertility, adoption, and parental planning services.
- Flexible paid time off.
- Monthly wellness stipend.
- Relocation stipend may be available.
- Expected to work from the office at least 3 days per week.
Skills
SQL, Data Modeling, Data Warehousing, dbt, Product Analytics, Data Science, Experimentation, Pricing Analytics, Monetization, Data Analysis
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