Senior Data Scientist

Our client operates in the healthcare IT industry, specializing in intelligent medication management that improves healthcare workflows and patient adherence to therapy. Its technology supports millions of patients annually, along with hundreds of thousands of prescribers and pharmacies, numerous electronic health record systems, and thousands of hospitals across the U.S. The organization addresses challenges related to prescription access, affordability, and adherence through end-to-end technology solutions.

About the Role

The Senior Data Scientist leads advanced AI, machine learning, and natural language processing initiatives that improve complex healthcare processes. This role drives technical innovation by developing, deploying, and maintaining production AI solutions while balancing clinical, regulatory, and operational requirements. The position collaborates closely with domain experts and engineering teams, influences technical direction, and ensures models meet high standards for quality, privacy, and reliability.

Responsibilities

• Lead end-to-end AI, machine learning, and NLP initiatives, including development, validation, deployment, monitoring, and maintenance.
• Apply large language models to automate high-volume workflows while balancing accuracy, latency, and cost.
• Create evaluation frameworks and datasets to measure model quality and identify performance regressions.
• Develop production-grade data pipelines while maintaining data quality, lineage, and reliability.
• Collaborate with clinicians, pharmacists, and other domain experts to establish ground truth and validate model performance.
• Ensure compliance with healthcare regulations, including HIPAA, with a strong focus on data privacy and safety.
• Serve as a technical lead by establishing project direction, engineering best practices, and approaches to complex problem-solving.
• Mentor and coach data scientists through technical reviews, feedback, and knowledge sharing.
• Communicate analytical findings and technical results effectively to technical and non-technical stakeholders, including executive leadership.

Requirements

• Master’s or Ph.D. in Computer Science, Data Science, Statistics, Mathematics, or a related field.
• Minimum 5 years of experience in data science, machine learning, and NLP, including production model deployment.
• Advanced proficiency in Python and SQL.
• Experience building ELT/ETL pipelines using tools such as dbt, Airflow, and AWS data services.
• Strong software engineering skills, including modular Python development, Git workflows, containerization, and CI/CD.
• Experience deploying and monitoring machine learning models on AWS using SageMaker, MLflow, or similar platforms.
• Expertise in developing LLM-powered applications, including prompt engineering and model evaluation.
• Proven ability to independently manage ambiguous and complex projects.
• Demonstrated leadership and mentoring capabilities.
• Excellent analytical, problem-solving, and communication skills suited to a fast-paced environment.