Data Scientist

Description

The company is a venture-backed healthcare startup that provides FDA-approved medication and clinical care for opioid use disorder (OUD) through telehealth. Its approach is discreet, convenient and affordable, and it operates in 16 states after almost six years.

The team includes physicians, scientists, entrepreneurs, researchers and former White House advisors, backed by technology and healthcare investors.

This is a fully remote role reporting to the Senior Director of Data. You will be the company's first dedicated data scientist and work as a peer to analysts and analytics engineers, shaping how modeling, experimentation and machine learning are done. Areas include clinical-capacity forecasting, no-show and retention prediction, outcome and risk models, and NLP on clinical documentation. You will work with Analytics Engineering to move models from notebooks to production and with the wider Technology Team to build data-driven decision-making that supports patient care.

Data is deeply embedded in the company culture, with wide use of data products and room to grow. Projects touch company-level KPIs, clinical, commercial and business operations, among others. The team works in agile sprints.

The Technology team encourages AI-assisted work with tools such as Claude and Gemini for coding, analysis and experimentation. The company treats AI as support for human judgment rather than a replacement. You will be expected to use AI well in your own work and help the wider technology team adopt it responsibly.

Experience in opioid treatment is not required, but knowledge of healthcare, including health outcomes, benchmarks, systems and HIPAA compliance, is preferred.

Responsibilities

• Build, validate and deploy predictive and statistical models, such as demand and clinical-capacity forecasts, no-show and retention risk, and outcome and risk predictions, that shape clinical and business strategy.
• Design and analyze experiments and quasi-experiments to measure true impact rather than correlation.
• Work with Analytics Engineering and Technology to deploy models into pipelines built on BigQuery, dbt and Dagster, with monitoring, retraining and drift detection so they keep working over time.
• Turn open clinical and operational questions into well-scoped, mathematically sound analyses with clear caveats.
• Act as the modeling partner for Clinical, Commercial and Business Operations, identifying high-value opportunities and explaining results in plain language.
• Serve as the subject-matter expert on statistical and machine learning methods and promote rigorous, evidence-based decisions across the team.

Requirements

• 3-5+ years of applied data science, with a solid grounding in statistics, probability, experimentation and machine learning. You know when a simple model is better than a complex one and can separate signal from noise.
• Advanced Python skills for data science, including pandas, scikit-learn, statsmodels, gradient boosting (LightGBM or XGBoost) and forecasting methods. R is a plus.
• Operations research experience is a strong plus: resource allocation, scheduling or optimization such as linear or integer programming, queuing theory or simulation, applied to clinical capacity planning.
• Comfort and enthusiasm with modern AI tools such as Claude, Cursor or Copilot to speed up coding, analysis and research, with the judgment to know when human review and validation matter.
• Ability to turn complex models into clear stories and actionable recommendations for non-technical audiences.
• Comfortable working with semi-structured data across many business domains and handling ambiguity.
• Interest in moving models from exploration into production with monitoring and retraining. Experience with orchestration tools such as Dagster or Airflow is a plus.
• Commitment to making evidence-based addiction treatment accessible. Experience in a regulated industry such as healthcare or fintech is a plus.
• Remote work from the United States.

Conditions

Salary range: $140,000 - $150,000 USD.

Pay is set by level and required skills, with a first-and-best offer approach, so no pay is held back and offers do not depend on negotiation. Pay may increase annually if the company performs well and meets its targets. Bands are available to discuss during interviews.

Equal opportunity commitment: the company welcomes applicants regardless of background.

Applications should reflect your own voice, since every application is read by a person.