About the company
This is a senior leadership opportunity to shape how analytics and data science drive product and growth strategy at a large-scale consumer technology organization.
Responsibilities
- Lead and develop decision scientists and data scientists, establishing a high quality bar while coaching team members toward greater technical expertise, strategic thinking, and leadership.
- Own the models and forecasts used to understand and predict monthly active user growth, including the key drivers behind acquisition, activation, engagement, retention, and churn.
- Lead exploratory and strategic analytics that identify opportunities to grow the user base and translate behavioral insights into actionable product and business priorities.
- Establish consistent standards for how analytical work is scoped, conducted, reviewed, communicated, and documented, ensuring quality and rigor across the team.
- Partner with Revenue Analytics and Data Engineering leadership to define common metrics, experimentation standards, and shared operating practices.
- Build an operating model that enables the analytics and data science organization to engage earlier in product and engineering roadmaps, influencing what should be built, measured, and tested.
- Apply AI-native approaches to analytical work, including coding agents, automated analysis, and intelligent tooling, while defining which activities should be automated and where human judgment remains essential.
- Bring strong inferential and causal thinking to product and growth questions, helping teams understand not only what users do but why they behave the way they do.
- Provide senior leadership with clear, evidence-based recommendations and determine which analytical questions deserve investment and which should not be pursued.
- Collaborate across a data-rich consumer technology environment involving billions of behavioral and location-related events, subscription activity, connected devices, and complex network effects.
Requirements
- 10+ years of experience in analytics, data science, decision science, or a closely related discipline, including at least 5 years in people management at a senior leadership level.
- Deep expertise in inferential and causal analytics, with the ability to lead and effectively challenge machine learning practitioners.
- Strong knowledge of engagement, retention, churn, cohort analysis, and other metrics used to understand consumer behavior and growth.
- Proven experience forecasting a company-level business metric and being accountable for the resulting outcomes.
- Strong technical proficiency with SQL and Python or R, combined with the ability to work confidently with modern data and analytics platforms.
- Experience with Databricks, experimentation platforms such as Statsig, Tableau or comparable BI tools, and AI-native analytics tools such as Hex or AI/BI.
- Hands-on experience using coding agents such as Claude Code or equivalent tools in analytical workflows, with a demonstrated willingness to work AI-first.
- Bachelor's degree or equivalent practical experience required; a master's degree or PhD in social science, psychology, behavioral science, or a related field is a plus.
- Demonstrated success transforming analytics teams from reactive request fulfillment into embedded, proactive strategic partners.
- Strong people-development skills, including a track record of growing analysts and data scientists into senior contributors and leaders.
- Experience establishing analytical standards, operating models, experimentation practices, and quality frameworks that teams consistently adopt.
- Strong curiosity about human behavior and the ability to formulate hypotheses rather than simply respond to data requests.
- Excellent executive communication, prioritization, influencing, and stakeholder-management skills, with the judgment to determine where the team should focus its resources.
- Experience working with product and engineering teams in an embedded model and familiarity with B2C subscription businesses is highly desirable.
- Familiarity with experimentation involving network effects is a plus.
Conditions
- US base salary range of $247,000–$366,000 USD, with final compensation determined by factors including location, experience, skills, and background.
- Comprehensive medical, dental, vision, life, and disability insurance, with plans fully paid for US employees.
- Equity as part of the overall compensation package.
- 401(k) plan with company matching.
- Paid parental leave.
- Mental Wellness Program and Employee Assistance Program.
- Flexible paid time off, company holidays, and summer and winter shutdown periods.
- Learning and development programs supporting ongoing professional growth.
- Equipment, tools, and reimbursement support for a productive remote working environment.
- Free premium membership and connected tracking.