Director, Principal Engineer, AI and Data Engineering

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 Commercial Creation Center and CDI organization (C4) 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. As the Director, Principal Engineer, AI and Data Engineering, you will be a leader within C4 team that leverages best practices from software engineering, data science, and analytics engineering to accelerate data-driven insight generation for the International Commercial business. In this role, you will be a technical advisor for developing and enhancing AI applications and integrating them into the enterprise analytics platform. You will help guide the strategic direction for AI within the International Commercial team while counseling business teams on how to evolve Pfizer International into a data-driven organization. In this process, you will work on diverse projects to close the loop between decisionmakers and data by leveraging software engineering best practices to develop applications with embedded AI. You will also integrate globally with Pfizer data science and AI teams to elevate AI assets to organizational or enterprise solutions for use at Pfizer. The ideal candidate is an expert in software engineering, data science, and AI with experience working in diverse and cross-functional teams, bridging the gap between data, technology, and people, to deliver the promise of AI to improve patients’ lives. ROLE RESPONSIBILITIES Provide thought leadership in developing scalable AI solutions for Pfizer International Commercial model Design and lead the delivery of end-to-end data science and AI solutions including overseeing data ETL pipelines, server-side logic, ML engineering, frontend development, visualization, IaC, and CI/CD deployment Lead AI solutions development workstreams by providing expertise, thought leadership, and embodying best practices to drive technical and strategic objectives Lead discussions in cross functional forums to clarify model design, deployment, insights, and highlight implications to all cohorts of users Communicate complex technical concepts and insights to both technical and non-technical stakeholders to influence strategic decision-making Conduct advanced data analysis, predictive analytics, and design algorithms to solve business problems Mentor junior team members through technical and organizational leadership Research and apply new algorithms, technologies, and analytics practices to achieve business and technical objectives Build a sense of trust and rapport that creates a comfortable and effective workplace, and an ability to work as part of an agile team (product owner, developers, etc.) Represent the company in industry events and help recruit top talent BASIC QUALIFICATIONS 10+ years of work experience as a software engineer and tech lead for a diverse range of projects 5+ years of hands-on expertise in AI, data science, or software development 2+ years experience as a back-end or full-stack senior/staff/principal software engineer Computer Science, Engineering, Mathematics, or Statistics majors with data science or software development specialization – Computer Science, Engineering, Analytics etc. Experience with the latest Large Language Models (LLM) public service API’s (OpenAI & Claude), prompt engineering techniques, agentic framework (LangChain, Autogen, etc.) and serving concepts (MCP, A2A, etc.) Demonstrated experience interfacing with other internal and external teams to incorporate their innovations and vice versa Experience in developing and operating analytic workflows and model pipelines that are parametrized, automated and reusable Experience developing and deploying data and analytic products for use by technical and non-technical audiences Understanding of data science development lifecycle (CRISP) Strong hands-on skills in ML engineering and data science (e.g., Python, industrialized ETL software) Experience with test-driven development and automated testing frameworks (e.g. pytest, pydantic) Strong hands-on skills in CI/CD integration (e.g. GitHub, GitHub Actions or Jenkins) Strong hands-on skills in a cloud based analytics ecosystem (AWS, Snowflake, etc) Fierce curiosity, strong analytical skills, and strong sense of ownership in problem solving Strong verbal and written communication skills with Chinese and English language proficiency PREFERRED QUALIFICATIONS Knowledge of business processes in commercial pharmaceutical domains would be strong plus Deep expertise with data science enabling technology, such as Dataiku Data Science Studio, AWS SageMaker, or other data science platforms Industry or consulting experience, along with project management skills strongly preferred Deep understanding of MLOps principles and tech stack (e.g. MLFlow) Experience in data ingestion, data warehousing, and data model concepts Strong hands-on skills for data pipeline orchestration (e.g. Airflow) Strong hands-on skills in containerization (e.g. AWS EKS, Kubernetes) Experience with big data technologies (e.g. Spark) Work Location Assignment: Hybrid Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates. 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