1 день назад
Staff Data Scientist (Product & Ops)
190 000 - 270 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Staff Data Scientist (Product & Ops) (Causal Inference/Product Analytics): Building rigorous statistical models, experimentation frameworks, and analytical recommendations for virtual behavioral healthcare with an accent on causal inference, experimentation, and cross-functional decision-making. Focus on designing scalable analytics systems, leveraging LLMs on text, and solving ambiguous product and operational questions that influence roadmaps and measurable outcomes.
Location: New York, NY; candidates within a 75-minute commute of the NYC office are expected to work onsite 4 days per week.
Salary: $190,000–$270,000 per year in target base compensation, determined based on location, experience, expertise, internal pay equity, and other business considerations.
Company
provides personalized virtual behavioral healthcare for people experiencing mental health conditions, substance use disorders, and eating disorders.
What you will do
- Partner with Product, Engineering, Design, Clinical, Operations, and Machine Learning teams to turn ambiguous questions into analytical recommendations.
- Build statistical models and analyses that identify roadmap priorities and support strategic decisions.
- Define meaningful metrics and influence leaders to adopt recommendations with measurable business and mission impact.
- Partner with Analytics and Data Engineering to design scalable analytical frameworks and enable self-service use of tools and methods.
- Apply causal inference methodologies, including experimentation, difference-in-differences, instrumental variables, and propensity scores.
- Serve as a technical lead for the Data Science organization and mentor peers.
Requirements
- 7+ years of experience in data science or analytics, including at least 3 years in a technical lead capacity.
- Experience navigating ambiguous data environments and providing statistically rigorous approaches to diverse stakeholders.
- Demonstrated experience with modeling that drove adoption of recommendations and measurable impact.
- Detailed knowledge of causal inference methods, including RCTs, difference-in-differences, IPW, propensity scores, instrumental variables, and variance reduction.
- Strong proficiency with SQL, Python or R, modern ELT/ETL, OLAP databases such as Snowflake, dbt, BI tools such as Tableau or Hex, and experimentation programs.
- Ability to communicate, collaborate, and influence business partners, including executives and Director-level stakeholders.
Nice to have
- Healthcare experience.
- Startup experience.
Culture & Benefits
- Work on mission-driven products focused on improving access to behavioral healthcare and patient outcomes.
- Comprehensive benefits for full-time, exempt employees.
- Values centered on connection, evidence-based thinking, curiosity, urgency, and persistence.
- Hybrid work arrangement with regular onsite collaboration for eligible candidates near the NYC office.
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