Job Description

Our client, a growing fitness/wellness tech company, is looking for a data loving Product Analyst with experience working with DTC brands to join their growing team!

You’ll turn numbers into clear, bite-sized insights that shape what we build next—and you’ll use modern large-language-model (LLM) tools to dig even deeper. Your work will guide the AI Coach, Community, Experience, and Platform pods.

This is a hybrid position based in NYC.

Responsibilities:

Track the right numbers - Decide which metrics really matter (activation, retention, session quality, etc.) and make sure we’re collecting clean, reliable data.

Dig into the data - Look at how people train, recover, and interact in the app. Use SQL and Python to spot patterns—and LLM-powered text tools to understand feedback, comments, or voice notes at scale.

Run and explain experiments -

• Set up A/B or multivariate tests: Split users into fair groups, roll out the new idea, and measure the difference.
• Keep it honest: Make sure the test is big enough and random enough to trust the results.
• Tell the story: Instead of saying “p-value < 0.05,” you’ll say “There’s a 95 % chance this change really boosts workout completion by 3 %.”
• Find the sweet spots: Use simple uplift / causal tools to see who benefits most, so we roll out winners to the right people first.

Build smart models - Create churn, LTV, or recommendation models—and prototype LLM workflows (e.g., retrieval-augmented answers from our knowledge base) that make the AI Coach smarter.

Share what matters - Build clear dashboards in Looker/Tableau/Metabase and craft short, visual write-ups so PMs, designers, and execs know exactly what to do next.

Champion data culture - Teach teammates how to read dashboards, run simple tests, and think about user impact before shipping.

Requirements:

• 2-4+ years in product or growth analytics (consumer tech; fitness or health-tech is a plus).
• Fluent in SQL and comfortable with Python (pandas, NumPy).
• Solid grasp of A/B testing basics and the ability to explain results in everyday language.
• Hands-on experience with LLM tooling—prompt design, embeddings, LangChain/LlamaIndex/TIA-S, or similar.
• Confident with BI tools (Looker, Tableau, Metabase).
• Great communicator who can turn complex data into clear recommendations.
• Genuine passion for wellness and helping people build healthy habits.

Preferred:

• Experience working with wearable or sensor data (Apple Health, Oura, WHOOP).
• Familiarity with data pipelines (dbt, Airflow) and cloud warehouses (BigQuery, Redshift).
• Background in behavioral science or UX research.

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