ROLE SUMMARYLeverage technical AI/ML/data science to guide critical decision-making processes in support of scientific and drug development strategies.
Collaborate with key stakeholders, business partners, and research teams to understand business problem, and implement new methods and techniques to solve novel problems
Lead cross functional projects / PoCs
ROLE RESPONSIBILITIESWork closely with global and regional teams to apply AI/ML innovative solutions to business problems and deliver on improving efficiencies in areas of drug development, e.g. in drug discovery, clinical trials, operational efficiencies
Translate business requirements into tangible solution specifications and high quality, on time deliverables
Work with internal and external partners to propose new solutions for solving novel problems
Lead cross functional projects to either implement existing solutions, or identify and create new solutions to solving problems in drug development
Support business process excellence by implementing, and creating new processes and pipelines
Support and lead ongoing technology evaluation process and cross functional proof of concept projects
Represent AQDS functions on cross-functional teams
Evangelize the use of AI/ML techniques, both internally and externally
BASIC QUALIFICATIONSAdvanced degree (Masters, PhD) in Computer Science, Data Science, Computation Biology, Statistics, or related field
8 - 10 yrs. of relevant experience for Masters level, Ph.D. with 3-5 years of experience
Python or R fluency
Ability to lead AI/ML/data science pipeline including the various steps of data retrieval, cleaning, analysis/modeling, application of AI algorithms through to production
Expertise with standard supervised and unsupervised machine learning approaches
Advanced verbal and written communication skills in relating to colleagues and associates both inside and outside the organization.
Ability to influence stakeholders when leading cross-functional projects
PREFERRED QUALIFICATIONSAbility to complement the team with new approaches such as Agentic AI, RAGs, LLMs, network analysis, knowledge graphs, graph neural networks, etc. would highly desired
Experience working in scalable computing would be a valuable supplement (AWS, Spark, Kubernetes, etc.)
Experience in data visualization, user interfaces (Flask, Shiny, etc.), data pipelines and MLOps are a plus
Knowledge of pharmaceutical area and chemistry/biology familiarity
PHYSICAL/MENTAL REQUIREMENTSKnowledge of state-of-the-art technologies and tools for AI/ML/Data Science/ Data Analytics/Statistics /; able to evaluate and leverage them into improved business processes for deployment and adoption
Expertise in some of the above mentioned tools/technologies
ORGANIZATIONAL RELATIONSHIPSWorks within DSA functional lines (Statistics, SDSA) and with functions in GPD
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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