Product Data ScientistDepartment: Data Engineering
Employment Type: Permanent - Full Time
Location: Remote USA - In Tandem
Compensation: $100,000 - $140,000 / year
DescriptionAs our
Product Data Scientist, you'll bring rigorous behavior analysis and predictive modeling to how our apps understand and serve our members - partnering closely with Product and Finance to turn millions of family interactions into models that shape both the product roadmap and the business strategy across OurFamilyWizard, Cozi, and FamilyWall.
What you will accomplish:Smart, personalized in-app experiences- Ship the models that power personalized in-app experiences - predicting what each member is likely to want next based on real-time behavior, family context, and engagement history.
- Detect meaningful patterns in product usage data - communication, scheduling, and activity signals - and build the models that turn those patterns into in-app suggestions, alerts, and guidance for families.
- Help replace fixed-placement UI logic with algorithmic decisioning that adapts every time someone opens the app.
Behavioral prediction and lifecycle ML - Build the churn, retention, and activation models that help Product understand which behaviors predict long-term value and which interventions are worth shipping.
- Develop predictive segmentation, propensity, and uplift models, refreshed continuously through automated pipelines so the rest of the business is always acting on current signal.
Strategic modeling for Finance - Partner with Finance on cohort-level subscriber and revenue forecasting, LTV by acquisition source, and sensitivity analysis on the assumptions that matter most.
- Build pricing, promo, and refund-risk models that quantify the financial impact of monetization decisions before we ship them.
Production ML pipelines - Train, deploy, and monitor models in Databricks and AWS, using Claude Code as your primary engineering interface.
- When agentic delivery makes sense, wrap models in managed agents that surface predictions into the workflows stakeholders already use.
Experimentation and causal rigor - Move the team from "what happened" to "what would happen if" - uplift modeling, geo-tests, and A/B analysis grounded in proper causal framing.
Who you are:- A modeler who thinks in patterns, hypotheses, and tests, and who owns problems end to end - from question framing through SQL, feature pipelines, modeling, serving, and stakeholder communication. You ship models real decisions depend on, not just notebooks and decks.
- Pragmatic about ML - you know when a model is worth building and when a heuristic does the job, and you translate a CFO's question and a PM's question with the same fluency.
- AI-first in how you build. Modern AI tooling - Claude Code, agent SDKs, coding agents - is part of your craft, and you operate at higher leverage because of it.
- Motivated by work that matters. Families rely on these products during real moments in their lives.
What you bring:- 5+ years shipping predictive models in production, ideally across personalization, behavioral prediction, lifecycle ML, or subscription forecasting.
- Strong Python and SQL. Hands-on experience with Databricks and AWS.
- Demonstrated success with subscription or consumer-app metrics - LTV, churn, retention, activation, forecasting.
- Solid grasp of experimentation and causal methods (A/B, DiD, uplift, geo-tests, or similar).
- Production rigor - feature pipelines, model monitoring, retraining cadence.
Here's a list of our key benefits: - Medical: In Tandem pays 100% of the premium for employees AND 99% for all additional family members
- 401k: Up to a 4% match with immediate vesting
- Paid leave for all new parents
- Learning & Development stipend for employees
- Paid Time Off: 11 Holidays + Winter Break (3 Days) + Volunteer Time Off (1 Day) + Floating Holiday (1 Day)
- Personal Time Off: 15 days for 0-1 years of employment, 20 days 1-3 years of employment
- Supportive and flexible working environment - work from anywhere!
