Data Scientist

Ophelia

. Build, validate, and ship predictive and statistical models for demand and clinical-capacity forecasting, no-show and retention risk, and outcome and risk prediction .

Posted 10/31/2026full-timeRemote • United StatesMid-LevelSenior💰 $140,000 - $150,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying predictive models using advanced statistical and machine learning techniques, with a strong foundation in Python and experience in production pipelines. Capable of translating complex analyses into actionable insights while collaborating effectively across clinical and operational domains.

Highest-signal resume keywords

Applied Data Science ExperienceStatistical AnalysisMachine Learning ProficiencyPython ML/Analysis StackModel Deployment in BigQuery

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Statistical ModelingMachine LearningData AnalysisExperiment DesignForecasting MethodsResource AllocationOptimization ProblemsMonitoring and RetrainingPandasScikit-Learn

Soft Skills

Clear CommunicationCollaborationProblem-Solving

Tools & Technologies

BigQueryDbtDagsterAirflowClaudeCursorCopilot

Industry Keywords

HealthcareFintechHIPAA ComplianceHealth OutcomesEvidence-Based Treatment

Tech Stack

Tools & technologies

AirflowBigQueryPandasPythonScikit-Learn

About the role

Key responsibilities & impact

Build, validate, and ship predictive and statistical models for demand and clinical-capacity forecasting, no-show and retention risk, and outcome and risk prediction
Design and analyze experiments and quasi-experiments to measure causal impact
Collaborate with Analytics Engineering and Technology teams to deploy models in BigQuery, dbt, and Dagster pipelines
Implement continuous monitoring, retraining, and drift detection for production models
Translate open clinical and operational questions into rigorous, well-scoped analyses
Partner with Clinical, Commercial, and Business Operations to identify opportunities and communicate results in plain language
Serve as the subject-matter expert for statistical and machine-learning methods
Help shape responsible and effective AI-augmented workflows across the Technology team
Report to the Senior Director of Data and work as a peer to analysts and analytics engineers

Requirements

What you’ll need

3-5+ years of applied data science experience
Strong foundation in statistics, probability, experimentation, and machine learning
Advanced proficiency in Python ML/analysis stack, including pandas, scikit-learn, statsmodels, LightGBM/XGBoost, and forecasting methods
Familiarity with R is a plus
Familiarity with resource-allocation, scheduling, or optimization problems is a strong plus
Comfortable and enthusiastic using modern AI tools such as Claude, Cursor, and Copilot
Ability to communicate complex modeling through clear narratives and actionable recommendations
Ability to work with semi-structured data and ambiguity across varied business domains
Interest in moving models into production pipelines with monitoring and retraining
Experience with orchestration tools such as Dagster or Airflow is a plus
Passion for evidence-based addiction treatment
Experience in a regulated industry such as healthcare or fintech is a plus
Healthcare landscape knowledge, including health outcomes, benchmarks, systems, and HIPAA compliance, is ideal but not required

Benefits

Comp & perks

Pay transparency and equity
First and best offer approach
Opportunities for increased compensation annually as the company performs well and meets targets
Fully remote position
AI-augmented ways of working with tools such as Claude and Gemini