Manager, Data Science Solution Engineer

ROLE SUMMARY

Do you want to make a global impact on patient health? Do you thrive in a fast-paced environment that integrates scientific, clinical, and commercial domains through engineering, data science, and AI? Join Pfizer Digital’s Artificial Intelligence, Data, and Advanced Analytics organization (AIDA) to leverage cutting-edge technology for critical business decisions and enhance customer experiences for colleagues, patients, and physicians. Our team of engineering, data science, and AI professionals is at the forefront of Pfizer’s transformation into a digitally driven organization, using data science and AI to change patients’ lives. The Data Science Industrialization team is a key driver of Pfizer’s digital transformation, leading process and engineering innovations to advance AI and data science applications from prototypes and MVPs to full production.

As a Manager, AI and Data Science Solution Engineer, you will join the Data Science Industrialization team. Your responsibilities will include architecting and implementing AI solutions and reusable AI components. You will iteratively develop and continuously improve data science workflows, AI use cases, and reusable components to accelerate use case delivery. 
 

ROLE RESPONSIBILITIES

• Develop scalable and reliable AI solutions and reusable software components.
• Implement robust technical strategies, including API integration, to connect reusable AI components with broader systems and deliver scalable AI solutions.
• Proactively identify and resolve potential system issues.
• Deliver scalable data pipelines that ingest and integrate data from various sources, providing high-quality data products for data science and AI applications.
• Build scalable ML pipelines based on available infrastructure.
• Conduct exploratory data analysis and quality checks.
• Create and maintain robust technical documentation for AI accelerators to ensure knowledge retention and sharing.
• Collaborate with AI use case development teams to integrate reusable components into production AI solutions.
• Partner with the AIDA Platforms team to integrate capabilities between enterprise platforms and internally developed reusable component accelerators (e.g., API registry, ML library/workflow management, enterprise connectors).

BASIC QUALIFICATIONS

• Bachelor's degree in AI, data science, or a related field (e.g., Data Science, Computer Engineering, Computer Science, Information Systems, Engineering).
• 5+ years of experience in data science, analytics, or solution engineering, with a proven track record of building and deploying complex software systems.
• Strong understanding of the Software Development Life Cycle (SDLC) and data science development lifecycle (CRISP).
• Experience working in a cloud-based analytics ecosystem (e.g., AWS, Snowflake).
• Highly self-motivated, capable of delivering both independently and through strong team collaboration.
• Ability to creatively tackle new challenges and step outside your comfort zone.
• Strong English communication skills (written and verbal).

PREFERRED QUALIFICATIONS

• Advanced degree in Data Science, Computer Engineering, Computer Science, Information Systems or related discipline.
• Experience in solution architecture & design.
• Experience in software/product engineering.
• Strong hands-on skills in ML engineering and data science (e.g., Python, R, SQL, industrialized ETL software).
• Experience with data science enabling technology, such as Dataiku Data Science Studio, AWS SageMaker or other data science platforms.
• Experience in CI/CD integration (e.g. GitHub, GitHub Actions or Jenkins).
• Deep understanding of MLOps principles and tech stack (e.g. MLFlow).
• Experience with Dataiku Data Science Studio.
• Hands on experience working in Agile teams, processes, and practices.

  
Work Location Assignment: Hybrid