Head of Data

This is a fully remote position, open to applicants in United States.

📋 Description

• Take ownership of the architecture and reliability of the UA data pipeline, encompassing BigQuery, dbt, Jenkins, AppsFlyer/SKAN attribution, along with our downstream dashboards and Mixpanel warehouse synchronization.

• Spearhead the migration of remaining Python transformation scripts into dbt; establish CI/CD processes, testing standards, and maintain development and production environment hygiene.

• Collaborate with engineering on the ingestion layer, which includes ad platform APIs, Firebase, and custom subscription backend webhooks, while ensuring upstream data quality.

• Assess and implement new tools when appropriate, while prioritizing simplicity in the tech stack.

• Manage the definitions, logic, and reliability of our core metrics, including installs, trials, trial-to-paid conversions, RPP, ROAS, CAC, LTV, and churn.

• Lead our attribution methodology, which includes MMP (AppsFlyer), SKAN 4, and SSOT deduplication, communicating this effectively to the UA and executive teams.

• Support our experimentation program by assisting PMs and the UA team in designing tests, validating results, and fostering statistical expertise across the organization.

• Have experience in building or managing experimentation infrastructure, including A/B testing platforms and frameworks for statistical significance.

• Create self-service data products that minimize the number of ad hoc requests directed towards the team, including AI-powered tools such as natural language querying over Mixpanel/BigQuery, automated anomaly detection, and LLM-assisted reporting where it adds significant value.

• Oversee the product analytics instrumentation strategy in collaboration with engineering, focusing on event taxonomy, Mixpanel governance, and Firebase event schema.

• Convert product analytics into actionable insights for PMs, covering retention curves, funnel analysis, feature adoption, and onboarding optimization.

• Ensure the product team can independently answer their questions without relying on the data team for every inquiry.

• Manage and nurture two data scientists, making hiring decisions to expand the team as necessary.

• Work closely with the UA Manager, Growth PM, and Head of Product as the primary business-facing contact for the data team.

• Establish sprint cadence, manage the data backlog, and keep the team focused on high-impact tasks.

• Drive data governance and the development of a semantic data layer, enhancing our visualization platform's usability for non-technical stakeholders.

• Assist the organization in identifying and automating high-friction internal workflows using AI, a company-wide priority with executive backing.

• Promote a culture of practical AI adoption within the data team and across the organization.

⛳️ Requirements

• Minimum of 7 years in data or analytics roles, with at least 2 years of experience managing a data team.

• Proficient in analytics engineering: a strong command of dbt, capable of reviewing SQL models and data pipelines, and able to assist engineers in troubleshooting issues.

• Comprehensive understanding of subscription and mobile app metrics, including trial conversion, trial-to-paid modeling, LTV, renewal rates, and cohort analysis.

• Experience with mobile UA attribution, including MMP (AppsFlyer, Adjust, or similar), SKAN, and the complexities of cross-platform reporting.

• Familiarity with BigQuery (or another cloud data warehouse) as the core analytical infrastructure.

• Strong instincts for data modeling: adept at thinking in terms of facts and dimensions, understanding grain, and explaining why a join may produce duplicate rows.

• Background in product analytics: experience owning event instrumentation, establishing governance frameworks in Mixpanel or Amplitude, and collaborating with product teams to derive insights from raw events.

• Excellent business partnering skills: ability to translate technical limitations into straightforward language for product and marketing stakeholders, and the confidence to challenge poorly framed questions.

• Product-oriented mindset: viewing data as a product that serves internal users rather than merely a function that responds to requests.

• Practical experience with AI/LLM tools: not just using tools like Copilot or ChatGPT for productivity, but also designing and implementing AI-assisted workflows, internal analytics agents, or data applications that minimize manual tasks. Knowledge of the capabilities of current models and innovative applications of these technologies.

🏝️ Benefits

• Competitive salary and compensation package.

• Comprehensive health, dental, and vision insurance.

• Retirement plan with employer matching contributions.

• Commuter and lunch benefits, including UberEats.

• Free access to telehealth and BetterHelp services.

• Provision of any necessary hardware or software to facilitate success.

• A product that is cherished by millions and recognized by the media.

• A team of amazing colleagues to collaborate with.

• The opportunity to help improve people's lives every day.