Data Scientist II

As a Data Scientist II, you will work in the heart of a cross-functional product team and help turn real-world signals into clear, decision-ready insights. You will partner with Product, Engineering, Design, Ops, and Clinical stakeholders to define questions, measure outcomes, run experiments, and surface what is working (and what is not). Over time, you will take on larger scopes and more ambiguity, and help operationalize stable insights through lightweight models or scoring approaches when appropriate.

This role is a strong fit for someone who wants to grow from strong executor to end-to-end owner, and who gets energy from using data to make things better for patients and providers.

• Be the analytics partner inside the pod. Support product decisions by clarifying goals, defining metrics, and translating business questions into analytical work.
• Run experiments with good hygiene. Help design and analyze A/B tests and quasi-experiments with clear hypotheses, success criteria, and guardrails.
• Understand user behavior and product performance. Use funnel, cohort, and lifecycle analysis to identify drop-offs, opportunities, and tradeoffs across the patient and provider journeys.
• Use causal methods when needed. Apply approaches like diff-in-diff, matching, and regression-based designs with support from more senior peers as appropriate.
• Build and maintain decision-ready assets. Create analysis, dashboards, and monitoring views that make performance visible and help teams move faster.
• Communicate clearly. Share findings in a way that is crisp, actionable, and honest about uncertainty.
• Contribute to team standards. Follow best practices for metric definitions, analysis quality, and experiment documentation, and help improve them over time.

• 3+ years using data to drive product or business decisions in product, growth, engineering, or operations environments (or equivalent experience).
• Strong SQL and proficiency in Python or R for analysis.
• Working knowledge of experimentation (test design, analysis, pitfalls) and curiosity to deepen that skill set. Bayesian experience is a plus, not a requirement.
• Comfort with common analytical techniques (cohorting, segmentation, regression, forecasting basics), plus an instinct for checking assumptions and data quality.
• Ability to translate messy questions into structured analysis and clear recommendations.
• Strong communication skills, especially with non-technical partners.
• High ownership and follow-through: you take responsibility for outcomes in addition to tasks.
• Motivation for our mission: improving access and affordability in mental healthcare.

Compensation and Benefits:

The expected base pay range for this position is $127,500 - $150,000, based on a variety of factors including qualifications, experience, and geographic location. In addition to base salary, this role may be eligible for an equity grant, depending on the position and level.

We are committed to offering a comprehensive and competitive total rewards package, including robust health and wellness benefits, retirement savings, and meaningful ownership opportunities through equity. Compensation decisions are made holistically, ensuring fairness and alignment with market benchmarks while recognizing individual contributions and potential.

• Benefits offered include:
• Equity compensation
• Medical, Dental, and Vision coverage
• HSA / FSA
• 401K
• Work-from-Home Stipend
• Therapy Reimbursement
• 16-week parental leave for eligible employees
• Carrot Fertility annual reimbursement and membership
• 13 paid holidays each year as well as a Holiday Break during the week between December 25th and December 31st
• Flexible PTO
• Employee Assistance Program (EAP)
• Training and professional development

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