Head of Data

BetterSleep

8h•$200,000 - $250,000

About The Position

BetterSleep is a leading sleep app with over 85 million downloads, seeking to transition from a legacy growth model to one focused on unit economics, demand quality, and sustainable acquisition. This role offers the opportunity to build the growth engine for a widely used brand, combining startup-level ownership with the resources of a public company. The team operates at the intersection of consumer product, performance marketing, and data science, aiming to enhance these areas through a robust data foundation. They manage sophisticated User Acquisition (UA) programs across various platforms (Facebook, Apple Search Ads, TikTok, CTV), run a continuous experimentation program for subscription pricing, onboarding, and content, and utilize a growing Firebase + BigQuery data platform. The team is characterized by its lean structure, high conviction, and rapid pace.

Requirements

7+ years in data/analytics roles.
At least 2 years managing a data team.
Hands-on analytics engineering experience with dbt.
Comfort reviewing SQL models and data pipelines.
Ability to unblock engineers when issues arise.
Deep understanding of subscription and mobile app metrics (trial conversion, trial-to-paid modeling, LTV, renewal rates, cohort analysis).
Experience with mobile UA attribution (MMP, SKAN, multi-touch) and cross-platform reporting.
Comfort with BigQuery (or another cloud data warehouse).
Strong instincts for data modeling (facts and dimensions, grain, understanding join issues).
Product analytics experience (event instrumentation, Mixpanel/Amplitude governance, translating events to insights).
Business partnering skills (translating technical constraints, pushing back on incorrect questions).
Product mindset: viewing data as a product for internal users.
Practical experience building with AI/LLM tools (designing and shipping AI-assisted workflows, internal analytics agents, data apps).

Nice To Haves

Background in consumer subscription apps (health, wellness, entertainment, productivity).
Experience building internal data apps using AI frameworks (Claude/OpenAI APIs, LangChain, agent tooling) such as dashboards, Slack bots, automated anomaly alerts, or natural language analytics interfaces.
Deep experience with attribution frameworks and data modeling.

Responsibilities

Own and evolve the entire data function at BetterSleep, including platform, people, and strategy.
Manage a team of data scientists.
Own the roadmap for the data infrastructure.
Serve as the strategic data partner to product, growth, and executive leadership.
Review dbt models, design data products, and unblock the data team.
Set direction and partner with the business on key decisions.
Lead the next phase of rebuilding the data team with a platform-first mindset, focusing on stable pipelines, reliable definitions, self-service tooling, and governance.
Own the architecture and reliability of the UA data pipeline (BigQuery, dbt, Jenkins, AppsFlyer/SKAN attribution, Mixpanel warehouse sync).
Drive the migration of Python transformation scripts into dbt and establish CI/CD, testing standards, and environment hygiene.
Partner with engineering on the ingestion layer (ad platform APIs, Firebase, custom subscription backend webhooks) and upstream data quality.
Evaluate and introduce new tooling while maintaining a simple stack.
Own the definitions, logic, and reliability of core metrics (installs, trials, trial-to-paid, RPP, ROAS, CAC, LTV, churn).
Lead the attribution methodology (MMP, SKAN 4, SSOT deduplication) and communicate it to UA and executive teams.
Support the experimentation program by helping design tests, validate results, and build statistical capabilities.
Build self-service data products to reduce ad hoc requests, including AI-powered tooling (natural language querying, anomaly detection, LLM-assisted reporting).
Own product analytics instrumentation strategy in partnership with engineering (event taxonomy, Mixpanel governance, Firebase event schema).
Translate product analytics into actionable insights for PMs (retention curves, funnel analysis, feature adoption, onboarding optimization).
Ensure the product team can answer their own questions independently.
Manage and develop two data scientists, and make hiring decisions for team expansion.
Partner closely with the UA Manager, Growth PM, and Head of Product as the primary business-facing contact for the data team.
Set sprint cadence, manage the data backlog, and keep the team focused on high-leverage work.
Drive data governance and data semantic layer development to improve the usability of the visualization platform for non-technical stakeholders.
Help the organization identify and automate high-friction internal workflows using AI.
Champion a culture of practical AI adoption within the data team and beyond.