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Salary: USD 140,000 - 150,000 / annual
Ophelia is a venture-backed healthcare startup providing FDA-approved medication and clinical care for opioid use disorder (OUD) through a telehealth platform. Operating in 16 states for nearly six years, the company combines physicians, scientists, entrepreneurs, and researchers to reimagine OUD treatment in America.
As Data Scientist, you will build statistical and machine-learning models that drive forward-looking business decisions. You'll develop forecasting models for clinical capacity and business operations, as well as marketing models to optimize conversion. Working in a fully remote position reporting to the Senior Director of Data, you'll be the company's first dedicated data scientist, shaping how modeling, experimentation, and machine learning are practiced across the organization.
Key responsibilities include:
- Building, validating, and shipping predictive and statistical models for demand forecasting, clinical-capacity planning, no-show and retention risk prediction, and outcome modeling
- Designing and analyzing experiments and quasi-experiments to measure true causal impact
- Productionalizing models into robust pipelines (BigQuery, dbt, Dagster) with continuous monitoring, retraining, and drift detection
- Translating open clinical and operational questions into well-scoped, mathematically sound analyses
- Partnering cross-functionally with Clinical, Commercial, and Business Operations teams to surface high-leverage opportunities
- Championing rigorous, evidence-based decision-making and raising the bar for statistical and ML methods
You'll collaborate closely with Analytics Engineering to move models from notebook to production, and with the broader Technology Team to embed data-driven decision-making throughout the organization. Ophelia actively encourages AI-augmented workflows, treating tools like Claude and Gemini as force multipliers for human judgment—you'll be expected to use AI fluently in your workflow while helping shape responsible organizational adoption.
While specific experience in addiction treatment is not required, knowledge of the healthcare landscape—including health outcomes, benchmarks, systems, and regulatory compliance (HIPAA)—is valued.
REQUIREMENTS:
- 3–5+ years of applied data science with strong foundation in statistics, probability, experimentation, and machine learning
- Advanced proficiency in Python ML/analysis stack (pandas, scikit-learn, statsmodels, gradient-boosting frameworks like LightGBM/XGBoost, forecasting methods); R familiarity is a plus
- Familiarity with operations research, resource allocation, scheduling, or optimization problems (linear/integer programming, queuing theory, simulation) is a strong plus
- Comfortable and enthusiastic about using modern AI tools (Claude, Cursor, Copilot) to accelerate work while applying judgment about when human review matters
- Strong communication skills: ability to translate complex modeling into clear narratives and actionable "so-what" recommendations for non-technical audiences
- Analytical versatility and comfort navigating ambiguity in semi-structured data environments spanning multiple business domains
- Interest in productionalizing models with monitoring and retraining; orchestration experience (Dagster, Airflow) is a plus
- Passion for making evidence-based addiction treatment accessible; experience in regulated industries (healthcare, fintech) is a plus
