Data Scientist

Ophelia

16h • $140,000 - $150,000 • Remote

About The Position

Ophelia is a venture-backed healthcare startup providing FDA-approved medication and clinical care for people with opioid use disorder through a telehealth platform. Its mission is to make evidence-based treatment accessible while respecting patients’ time and dignity. The company operates in 16 states and brings together physicians, scientists, entrepreneurs, researchers, and others to reimagine OUD treatment.

The Data Scientist will build statistical and machine-learning models that turn company data into forward-looking decisions, including operational forecasting and marketing models to drive conversion. The role translates open operational and growth questions into rigorous, well-scoped models that are put into use. Work will inform company-level KPIs, clinical and commercial efforts, and business operations.

This is a fully remote position reporting to the Senior Director of Data and working as a peer to analysts and analytics engineers. As Ophelia’s first dedicated data scientist, the person in this role will help shape modeling, experimentation, and machine-learning practices. Areas of potential work include clinical-capacity forecasting, no-show and retention prediction, outcome and risk models, and NLP on clinical documentation. The role partners with Analytics Engineering to move models into production and with the broader Technology Team to strengthen data-driven decision-making and patient care.

Ophelia encourages AI-augmented work and expects the Data Scientist to use AI tools fluently and help shape their responsible and effective use across the Technology team. The work involves collaborating across teams, delivering high-quality work using an agile methodology, and communicating findings in a clear, actionable way. Experience in addiction treatment is not required; healthcare knowledge, including outcomes, benchmarks, systems, and HIPAA compliance, is desirable.

Requirements

• 3–5+ years of applied data science experience and a strong foundation in statistics, probability, experimentation, and machine learning.
• Advanced proficiency in Python data science and machine-learning tools, including pandas, scikit-learn, statsmodels, gradient-boosting frameworks such as LightGBM or XGBoost, and forecasting methods.
• Ability to choose appropriate model complexity and distinguish signal from noise.
• Comfort working with semi-structured data, a wide variety of business domains, and ambiguous projects.
• Ability to communicate complex modeling clearly and provide actionable recommendations to non-technical audiences.
• Comfort and enthusiasm using modern AI tools to accelerate coding, analysis, and research, with sound judgment about human review and validation.
• Interest in taking models from exploration into production pipelines with monitoring and retraining.

Nice To Haves

• Familiarity with R.
• Familiarity with resource allocation, scheduling, or optimization, such as linear or integer programming, queuing theory, or simulation.
• Experience with orchestration tools such as Dagster or Airflow.
• Experience in a regulated industry such as healthcare or fintech.
• Knowledge of the healthcare landscape, including health outcomes, benchmarks, systems, and HIPAA compliance.
• Passion for making evidence-based addiction treatment accessible.

Responsibilities

• Build, validate, and deploy predictive and statistical models, including demand and clinical-capacity forecasts, no-show and retention risk models, and outcome and risk prediction models.
• Design and analyze experiments and quasi-experiments to measure impact rather than correlation.
• Partner with Analytics Engineering and Technology teams to deploy models in robust pipelines using BigQuery, dbt, and Dagster, with monitoring, retraining, and drift detection.
• Translate open clinical and operational questions into well-scoped, mathematically sound analyses with clear caveats.
• Partner with Clinical, Commercial, and Business Operations teams to identify high-leverage opportunities and communicate results in plain language.
• Serve as a subject-matter expert in statistical and machine-learning methods and champion rigorous, evidence-based decision-making.
• Use AI tools in the data science workflow and help shape their responsible and effective use across the Technology team.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed