Engineer I, Data Scientist

As Engineer I, Data Scientist, you will develop advanced analytics, machine learning, and AI solutions for the US Vaccines business.

You will work with complex healthcare datasets, build scalable analytical solutions, and partner with cross-functional stakeholders to translate data into actionable business insights.

The role also offers the opportunity to develop AI agents and agentic workflows, helping automate and scale the AI/ML lifecycle from data preparation and model validation through insight generation.

Key Responsibilities:

• Develop and deliver advanced analytics, machine learning, and statistical models across areas including customer segmentation, impact measurement, omnichannel analytics, resource allocation and budget optimization, and experimental design and test/control analysis.
• Design and build AI agents and agentic workflows, including LLM-based solutions, to automate data extraction, model validation, and insight generation.
• Identify opportunities to apply machine learning and advanced analytics to complex business challenges and unmet patient needs.
• Analyze patient, HCP, health system, and other healthcare datasets to uncover actionable insights.
• Partner with business and analytics stakeholders to translate business needs into effective data science solutions.
• Develop project plans, identify required inputs, and deliver high-quality analytical solutions against agreed milestones.
• Collaborate across cross-functional teams and provide data science subject matter expertise.
• Communicate complex analytical findings through compelling data storytelling and visualization, enabling data-driven decision-making.
• Contribute to data science best practices and knowledge sharing across the organization.

Required Qualifications:

• Bachelor’s degree with 5+ years of relevant industry experience.
• 5+ years of experience applying analytics, statistical methods, or data science techniques in a business environment.
• Strong proficiency in Python, SQL, PySpark, and data visualization tools.
• Experience developing and applying statistical and machine learning models.
• Hands-on experience building or deploying AI agents, agentic workflows, or LLM-based solutions to automate and scale elements of the AI/ML lifecycle.
• Ability to proactively identify analytical opportunities and apply machine learning and statistical approaches to solve complex problems.

Benefits:

• Opportunity to work on complex healthcare datasets and develop innovative solutions
• Collaborative and dynamic work environment
• Opportunity to contribute to data science best practices and knowledge sharing across the organization