Senior Product Data Scientist

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October 10

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Talkiatry

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Healthcare Insurance • Telecommunications • Wellness

Talkiatry is a virtual mental health care provider offering online psychiatry services. It specializes in the diagnosis and treatment of various mental health conditions including anxiety, ADHD, bipolar disorder, depression, OCD, PTSD, and more. With a large team of expert psychiatrists, Talkiatry provides virtual visits that are covered by insurance, making mental health care more accessible. Patients can complete an online assessment to connect with a psychiatrist and receive personalized treatment plans, which may include medication and supportive therapy. Talkiatry aims to ease access to mental health care through flexible scheduling and personalized care, supporting over 175,000 people to date.

501 - 1000 employees

⚕️ Healthcare Insurance

📡 Telecommunications

🧘 Wellness

📋 Description

• 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.

🎯 Requirements

• 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, statsmodels and all other common data science packages) and SQL; experience with modern data warehouses (Snowflake, Redshift, BigQuery). • Strong foundation in experimental design, causal inference, and statistical methods. • Practical understanding of ML modeling trade-offs: when to deploy advanced models vs. when a well-structured analysis is the right tool. • Understands the spirit of George Box’s reminder that “all models are wrong, but some are useful” and applies that judgment to build solutions that balance sophistication with pragmatism. • Exceptional communication skills, displaying the ability to frame technical findings in a way that resonates with stakeholders. • Experience in DBT is a plus, but not required. • Experience on a Product growth team, where experimentation and opportunity identification were key aspects of the role, is a plus. • Strong applied experience in data science is essential; a Master’s or PhD in a quantitative field is a plus

🏖️ Benefits

• Excellent benefits: medical, dental, vision, effective day 1 of employment • 401K with match • Generous PTO plus paid holidays • Paid parental leave