Senior Data Scientist, Life Sciences Technology Solutions

Job Family :

Travel Required :

Clearance Required :

What You Will Do :

The Senior Data Scientist, Life Sciences Technology Solutions, is responsible for designing, developing, and operationalizing data products, machine learning models, and AI-enabled capabilities within scalable technology platforms for biopharma clients. This role sits at the intersection of advanced analytics, AI/ML, and software-enabled delivery, embedding data-driven intelligence directly into applications, workflows, and decision systems.

The Senior Data Scientist works within cross-functional teams including product managers, engineers, and consultants to translate complex healthcare data into production-ready solutions. Success in this role is defined by the ability to build robust, reusable models and data assets that power real-time insights, support decision-making, and scale across clients and use cases.

Design and develop data products and machine learning models embedded within client-facing platforms and applications.

Operationalize analytics by integrating models, algorithms, and data pipelines into production systems and workflow-driven applications.

Work with large-scale healthcare datasets (e.g., claims, EMR, and external data sources) to enable scalable insight delivery within platforms.

Build and validate predictive, descriptive, and segmentation models that support decision systems across commercial, market access, and medical use cases.

Contribute to development of AI/ML-enabled applications, including GenAI, RAG pipelines, and agent-based workflows, ensuring outputs are scalable, traceable, and production-ready.

Collaborate with engineers and architects to deploy models via APIs, microservices, and cloud-based environments.

Develop modular, reusable code, data pipelines, and feature libraries that can be leveraged across multiple solutions.

Translate complex analytical logic into clear, user-facing outputs within applications, dashboards, and automated workflows.

Ensure data quality, model performance, and governance standards across deployed solutions.

Contribute to innovation and development of next-generation data products and analytics capabilities across the technology portfolio.

What You Will Need :

Master’s degree or PhD in Data Science, Statistics, Computer Science, Engineering, or a related quantitative field.

8+ years of experience developing and deploying AI/machine learning solutions in production environments.

Strong experience working with large-scale healthcare or life sciences datasets (e.g., claims, EMR, or similar).

Proficiency in Python and/or R, with strong SQL skills and experience building data pipelines.

Experience deploying models within cloud environments (Azure, AWS, or GCP).

Familiarity with API-based model deploy