Senior Data Scientist

Description

The company is building predictive intelligence products for its copay program, focused on affordability, reimbursement dynamics and patient access.

The work turns large healthcare datasets, including claims, enrollment and patient-level data, into scalable AI-powered tools that identify opportunities and support proactive decisions.

You will work with data engineering, business stakeholders, technology teams and analytics partners across the full lifecycle of AI and machine learning product development.

The role sits in the company's Analytics & AI organization and contributes to a long-term strategy for copay program intelligence.

Responsibilities

• Lead the design, development, deployment and ongoing improvement of advanced analytics and AI solutions for copay intelligence.
• Build and refine machine learning and AI models that address healthcare affordability, including predictive models that surface risks, patterns and opportunities.
• Create scoring frameworks, recommendation engines and decision-support systems that drive proactive business action.
• Evaluate and adopt modern methods such as machine learning, deep learning, ensemble methods, graph analytics and Generative AI.
• Improve model performance through experimentation, feedback loops and monitoring.
• Analyze large, complex healthcare datasets for actionable insights, using feature engineering, forecasting, segmentation, optimization and statistical analysis.
• Assess models with both statistical and business outcome metrics, and develop methods to measure business impact and return on investment.
• Turn vague business questions into defined analytical problems, hypotheses and success measures with stakeholders.
• Deploy machine learning solutions to production with data engineering and technology teams, including scalable pipelines, monitoring, automated retraining and governance.
• Apply sound practices for reproducibility, code quality, documentation, validation and responsible AI, and ensure solutions meet standards for privacy, security and compliance.
• Help build enterprise AI products that can scale across several business functions.
• Present findings and trade-offs to senior leaders, technical teams and business stakeholders, and act as a subject matter expert in data science and predictive analytics.
• Mentor junior data scientists and keep up with emerging AI, machine learning and healthcare analytics trends.

Requirements

• Bachelor's degree in Statistics, Computer Science, Data Science, Mathematics, Engineering, Economics, Operations Research or a related quantitative field.
• A Master's or PhD is preferred but not required. Equivalent combinations of education, specialized training and professional experience will be considered.
• 6+ years developing and deploying machine learning, AI or advanced analytics solutions in production, with proven results against business outcomes.
• Strong Python and SQL skills.
• Hands-on experience with frameworks such as Scikit-Learn, XGBoost, LightGBM, TensorFlow or PyTorch.
• Experience building predictive, classification, forecasting, recommendation or optimization models.
• Strong grounding in statistics, experimentation, predictive modeling and model evaluation.
• Experience with large-scale data platforms and cloud environments.
• Familiarity with MLOps, model deployment, monitoring and production AI practices.
• Experience with modern software development and version control.
• Strong analytical and problem-solving skills, with the ability to turn business challenges into data-driven solutions.
• Excellent communication and stakeholder management skills.
• Ability to work independently while collaborating well across teams, with strong organizational and project management skills.
• Enthusiasm for innovation, continuous learning and applying AI in practice.
• Preferred: experience with healthcare, pharmaceutical, claims, payer, patient support or market access data.
• Preferred: experience developing AI-powered decision support systems.
• Preferred: experience with AWS, Azure or Google Cloud.
• Preferred: experience with Snowflake, Databricks, Spark or other large-scale data environments.
• Preferred: experience deploying Generative AI or Large Language Model solutions.
• Preferred: experience in regulated industries where data quality, governance and validation are critical.
• Preferred: experience rapid-prototyping or evaluating generative AI solutions.
• Preferred: experience with experimentation or causal measurement methods.

Conditions

Pay disclosure applies only in locations with pay transparency requirements under state or local law. The posted base pay range is the company's good-faith estimate for this grade at posting time, and actual pay depends on factors such as geographic location and may fall outside it.

Any bonus, commission, incentive or other compensation is at the company's sole discretion until paid, and may change consistent with applicable law.

The role is open only to applicants in the US and Puerto Rico.

The company is an equal opportunity employer, including for veterans and disabled applicants.

Benefits

• Comprehensive benefits including paid time off (vacation, holidays and sick leave), medical, dental and vision insurance, and a 401(k) for eligible employees.
• Eligibility for long-term incentive programs.