AI Engineer responsible for developing and optimizing AI models for data analytics and supply chain at Pfizer. Collaborating with teams to drive innovation and improve patient outcomes.
Responsibilities
Responsible for data modeling and engineering within the advanced data platforms teams to achieve digital outcomes.
Create test plans, test scripts, and perform data validation.
Conceive, design, and implement Cloud Data Lake, Data Warehouse, Data Marts, and Data APIs.
Develop complex data products that are beneficial for PGS and Allow for reusability across enterprise.
Ability to collaborate with contractors to deliver technical enhancements.
Develop automated systems for building, testing, monitoring, and deploying ETL data pipelines within a continuous integration environment.
Develop internal APIs and data solutions to enhance application functionality and facilitate connectivity.
Collaborate with backend engineering teams to analyze data, enhancing its quality and consistency.
Conduct root cause analysis and address production data issues.
Design, develop, and implement AI models and algorithms to solve sophisticated data analytics and supply chain initiatives.
Stay abreast of the latest advancements in AI and machine learning technologies and apply them to Pfizer's projects.
Provide technical expertise and guidance to team members and stakeholders on AI-related initiatives.
Document and present findings, methodologies, and project outcomes to various stakeholders.
Integrate and collaborate with different technical teams across Digital to drive overall implementation and delivery.
Ability to work with large and complex datasets, including data cleaning, preprocessing, and feature selection.
Requirements
A bachelor's or master’s degree in computer science, Artificial Intelligence, Machine Learning, or a related discipline.
3+ years of experience as a Data Engineer, Data Architect, or in Data Warehousing, Data Modeling, and Data Transformations.
Over 1 years of experience in AI, machine learning, and large language models (LLMs) development and deployment.
Proven track record of successfully implementing AI solutions in a healthcare or pharmaceutical setting is preferred.
Strong understanding of data structures, algorithms, and software design principles.
Experience in Python, SQL, and familiarity with Java or Scala.
Familiarity with Hadoop, Spark, and Kafka for big data processing.
Benefits
Health insurance
Flexible working hours
Professional development opportunities
Job title
Senior Associate, Data Engineer – AI and Automation
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