Staff Data Scientist (Product & Ops)

charliehealth; Stati Uniti; Remoto; USD 190.000 - 270.000; Tempo pieno

Descrizione del lavoro

Charlie Health is seeking a senior data science partner to guide analytics across product, engineering, and clinical operations. You will mentor peers, shape the data science direction, and translate business questions into rigorous analyses with practical recommendations.

Responsibilities include defining metrics, influencing roadmaps, and developing Bayesian and causal models to drive measurable outcomes. The role requires onsite work in New York City four days a week from qualified candidates.

Competenze

• Seven+ years in data science/analytics with a technical lead track record.
• Ability to translate ambiguous problems into actionable analyses.
• Proven impact from modeling or analysis on decisions or outcomes.
• Deep knowledge of causal inference methods (randomized trials, diff-in-diff, weighting, propensity scores, IV).
• Proficiency with SQL and Python or R; experience with modern data workflows and DBT.

Mansioni

• Guide data science across product and operations to shape priorities and decisions.
• Define metrics, present evidence to leaders, influence roadmaps.
• Develop statistical models and analytical approaches for measurable impact.
• Apply Bayesian and frequentist methods and guide causal analysis.
• Collaborate with analytics and data engineering to build repeatable self-service analysis.

Conoscenze

Data leadership

Statistical modeling

Bayesian methods

Causal inference

SQL

Python/R

BI tooling

Communication

Strumenti

dbt

OLAP

BI tools

Descrizione del lavoro

Role overview

Guide data science across product and operations by turning uncertain business questions into rigorous analysis and practical recommendations. As a senior technical partner to leaders and teams spanning product, engineering, clinical work, and operations, you will shape priorities, improve decision-making, and mentor peers while helping establish the data science function’s direction.

Responsibilities

• Translate ambiguous questions from business and clinical partners into analyses and recommendations that inform strategy.
• Define useful metrics, present evidence to leaders, and influence decisions and roadmaps.
• Develop statistical models and analytical approaches that lead to adopted recommendations and measurable outcomes.
• Apply Bayesian and frequentist methods, and guide causal analysis using approaches such as experimentation, difference-in-differences, instrumental variables, and propensity scores.
• Work with analytics and data engineering to build repeatable frameworks and enable responsible self-service analysis.
• Use language models to extract insights from text, and mentor data science peers while helping shape team practices.

Requirements

• At least seven years in data science or analytics, including three years in a technical lead capacity.
• Strong experience navigating ambiguous data environments and communicating statistically sound approaches to varied stakeholders.
• Examples of modeling or analysis that led to adopted recommendations and visible impact.
• Detailed knowledge of causal inference methods, such as randomized trials, difference-in-differences, inverse probability weighting, propensity scores, instrumental variables, and variance reduction.
• Technical proficiency with SQL, Python or R, modern data transformation workflows, OLAP databases, dbt, and BI tools; experience scaling experimentation programs.
• Strong communication and influencing skills, especially with senior leaders.
• Candidates within a 75-minute commute of the New York City office are expected onsite four days per week.

Nice to have

• Healthcare or startup experience, and interest in applying data science to improve healthcare outcomes.

Benefits and work setup

• Target base salary is $190,000–$270,000 annually, determined by factors including experience, expertise, and level. Additional compensation may include stock options and benefits for full-time employees.