Senior Product Data Scientist
Listed on 2026-01-07
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IT/Tech
Data Analyst
We are looking for a Sr. Product Data Scientist to join our growing Data team in our Product organization. This is a senior individual contributor role with broad scope across product insights, experimentation, modeling and applied analytics focusing on growth. The ideal candidate is not only technically strong, but also proactive in uncovering opportunities, framing insights, and ensuring leaders have the context they need to make the right calls.
We are looking for this individual to bring analytical thought leadership as we continue to rapidly grow and iterate on our product offerings across Talkiatry.
You’ll own projects that range from producing growth and performance analyses that guide strategic and product decisions, to designing and evaluating experiments, to building predictive models, and to improving patient engagement and clinical efficiency. You’ll be expected to communicate insights proactively, frame results in business terms, and work closely with your core cross‑functional teammates (Product, Engineering and Design) as well as stakeholders across Operations, Clinical, and Finance.
AboutTalkiatry:
Talkiatry transforms psychiatry with accessible, human, and responsible care. We’re a national mental health practice co‑founded by a patient and a triple‑board‑certified psychiatrist to solve the problems both groups face in accessing and providing the highest quality treatment.
60% of adults in the U.S. with a diagnosable mental illness go untreated every year because care is inaccessible, while 45% of clinicians are out of network with insurers because reimbursement rates are low, and paperwork is unduly burdensome. With innovative technology and a human‑centered philosophy, we provide patients with the care they need—and allow psychiatrists to focus on why they got into medicine.
Youwill:
- Proactive Insights & Storytelling
- Identify growth opportunities for the Product teams by analyzing data and understanding patient behaviors.
- Help Product teams maximize impact, by working with PMs and engineers to understand costs and constraints, while looking at underlying data and making reasonable assumptions to size opportunities.
- Identify risks by exploring data and monitoring trends to understand the impact of emerging issues before they become problems.
- Frame analyses and estimates in terms of “so what” for the practice to ensure findings don’t just inform, but influence the team.
- Develop regular deliverables that turn historical data into forward‑looking guidance for product and operational teams.
- Anticipate questions our teams should be asking and bring forward insights before they’re requested.
- Modeling & Prediction
- Build, evaluate, and productionalize models to forecast outcomes such as patient retention, no shows, demand patterns, and more.
- Balance technical sophistication with pragmatic application, recognizing when simpler analyses can achieve the same business impact.
- Experimentation & Measurement
- Partner with Product and Operations teams to design experiments, define success metrics, and implement robust statistical evaluation frameworks.
- Ensure appropriate statistical power, so results are both valid and actionable.
- Analyze experiment results and establish clear post‑experiment communication, ensuring learnings (positive or negative) are codified and inform future product or operational decisions.
- Applied Analytics
- Lead analyses on patient growth, clinician utilization, marketplace dynamics and more to surface actionable insights to leadership.
- Translate adhoc analyses into repeatable frameworks and scalable reporting so insights don’t stay one‑off, but become institutional knowledge.
- Collaboration
- Collaborate with Data Engineering and BI teams to define requirements and highlight gaps, so that data pipelines reliably support advanced analytics and modeling.
- Act as a thought partner to Operations, Clinical, and Finance leaders, not just answering questions, but shaping the questions we should be asking.
- 4+ years of experience in data science, analytics, or related fields, with a track record of delivering measurable business impact.
- Advanced proficiency in Python (pandas, scikit‑learn,…
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