AI and Analytics Data Engineer building high quality data science pipelines for Pfizer's Digital Commercial Creation Center. Collaborating with global teams and defining ML Ops best practices for production analytics workflows.
Responsibilities
Building and automating high quality data science pipelines that power key business applications with advanced analytics/AI/ML
Defining and maintaining ML Ops best practices and deploying and maintaining production analytics and data science modeling workflows
Converting data/ML pipelines into scalable pipelines based on the infrastructure available
Enabling production models across the ML lifecycle
Determining model performance metrics and implementing monitoring dashboards
Designing champion/challenger model and A/B testing automation
Implementing CI/CD orchestration for data science pipelines
Managing the production deployments and post-deployment model lifecycle management activities
Working with stakeholders to assist with ML pipeline-related technical issues
Partnering with teams to integrate developed ML pipelines into enterprise-level analytics data products where appropriate
Requirements
Bachelor’s degree in ML engineering related area (Data Science, Computer Engineering, Computer Science, Information Systems, Engineering or a related discipline)
5-10 years of work experience in Data science, Analytics, or Engineering for a diverse range of projects
Understanding of data science development lifecycle (CRISP)
Strong hands-on skills in ML engineering and data science (e.g., Python, R, SQL, industrialized ETL software)
Experience working in a cloud based analytics ecosystem (AWS, Snowflake, etc)
Highly self-motivated to deliver both independently and with strong team collaboration
Ability to creatively take on new challenges and work outside comfort zone
Strong English communication skills (written & verbal)
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