ROLE SUMMARY The Global Commercial Analytics GCA team within the organization is dedicated to transforming data into actionable intelligence enabling the business to remain competitive and innovative in a datadriven world Are you passionate about using Data science AI and autonomous agents to unlock the return on every marketing dollar Do you thrive where advanced analytics agentic AI and commercial strategy meet Join our team as a Senior Manager Data Science and AI where you will lead the design development and deployment of AIsolutions that measurably improve how the business invests across channels As a Senior Manager for Data Science AI within GCA you are the technical cornerstone of Pfizers AI transformation You dont just govern or advise you to design build and prove You own the endtoend technical architecture of AI initiatives from data ingestion and model selection through RAG pipelines agent orchestration and production deployment You are equally credible in a whiteboard session and in a code review and you set up the bar for engineering quality across the team You partner directly with the International Commercial AI leadership program managers and business sponsors to translate ambitious commercial goals into sound scalable and compliant technical solutions You are not a manager who delegates the hard parts you are the person the team turns to when the architecture is unclear the data is messy or the model isnt behaving ROLE RESPONSIBILITIES 1 Technical Architecture Design Define and own the endtoend AI architecture for commercial initiatives from raw data through model inference and application layer Design and implement RetrievalAugmented Generation RAG systems including chunking strategies embedding pipelines vector store selection and retrieval optimization Architect multiagent and agentic orchestration systems using frameworks such as LangChain LlamaIndex AutoGen or CrewAI define agent roles tool use memory and humanintheloop patterns Select and configure Large Language Models LLMs including finetuning prompt engineering and context management for commercial use cases such as content generation summarization and intelligent search Design scalable data architectures that support AI workloads data lakes feature stores vector databases structured and unstructured data pipelines Evaluate and recommend LLM deployment strategies cloudhosted APIs OpenAI Azure OpenAI AWS Bedrock GCP Vertex AI selfhosted models and hybrid approaches 2 HandsOn Development Delivery Write review and own productionquality code across the AI stack Python SQL orchestration frameworks and infrastructureascode Build and maintain MLOps pipelines model training evaluation versioning CI CD for AI and monitoring in production drift detection hallucination guardrails latency tracking Develop and integrate APIs and automation workflows that connect AI capabilities to commercial business tools CRM content platforms regulatory review systems Conduct and lead technical design reviews architecture decision records ADRs and code reviews to ensure quality security and maintainability Prototype rapidly and iterate build proofofconcepts that stresstest assumptions before committing to fullscale implementation 3 Data Architecture Engineering Own the datastrategy for AI initiatives schema design data quality lineage governance and access controls Build and optimize data pipelines that ingest transform and serve both structured and unstructured data for model training and inference Apply expertise in embedding models and semantic search to create knowledge bases that power RAG and intelligent retrieval systems 4 Technical Leadership CrossFunctional Partnership Set the technical direction for AI initiatives define standards patterns and reusable components that accelerate delivery across the portfolio Mentor and coach senior engineers AI developers and data scientists elevate the overall technical capability of the Commercial AI team Translate complex technical concepts clearly to nontechnical stakeholders business sponsors program managers and governance bodies Represent the AI architecture function in enterprise governance forums and crossfunctional technical councils 5 Innovation Continuous Improvement Continuously evaluate emerging LLM frameworks foundation model releases vector database advancements and agent architectures for applicability to Pfizers commercial context Drive hackathons proofofconcepts and vendor evaluations to discover and validate current technical approaches Capture and institutionalize architectural learnings runbooks and reusable patterns for the broader AI portfolio Champion responsible AI practices bias evaluation output validation explainability and ethical use frameworks BASIC QUALIFICATIONS Bachelors or masters degree in

📌 Senior Manager Data Science and AI (Mumbai)
🏢 856 Pfizer Products India
📍 Mumbai