Manager, Senior Machine Learning Engineer
Thessaloniki Chortiatis, Greece
πριν από 1 μέρα

The Enterprise Platforms & Security (EP&S) team delivers the following capabilities for Pfizer - Business application platforms supporting Pfizer’s enterprise application and critical business processes.

Infrastructure allowing business traffic to travel where it needs to go, internally and externally, along with the appropriate access controls.

EP&S secures Pfizer's most important information assets through world class controls and protections and enables Pfizer's business results by making security an enabler and not a roadblock to achieving business results.

As a Senior Machine Learning Engineer, you will be responsible for developing and maintaining a machine learning operations (MLOps) foundation and framework as part of an analytics platform.

You will build and maintain solutions to support automation use cases as well as predictive modeling to avoid critical outages.

You will advance your data science skills, support the data science development practices of the team, and collaborate closely with others.


  • Provide best practices, guidance, and support to data science team : data versioning, model tracking, experiment tracking and code bundling for ease-of-deployment
  • Convert developed data / ML pipelines into scalable pipelines based on the infrastructure available
  • Develop continuous monitoring & training pipelines allowing model training in production by collaborating with data science team
  • Determine model performance monitoring metrics
  • Determine retraining trigger mechanism
  • Design champion / challenger model and A / B Testing
  • Develop CI / CD orchestration for the data science training pipeline
  • Coach members, share knowledge, and support the continuous development of our tooling within the broader team
  • Must-Have

  • BS in computer science, data science, or an engineering field.
  • At least 5 years of experience in data and analytics field
  • Experience in Machine Learning and Artificial Intelligence methodologies (e.g., Supervised / unsupervised learning, deep learning, natural language processing), ML development tools and data pipeline tools
  • Strong understanding of data science development lifecycle (CRISP)
  • Strong hands-on skills in software engineering (e.g., Python)
  • Deep understanding of MLOps principles and tech stack (e.g., MLFlow)
  • Strong experience with SQL and Python.
  • Nice-to-Have

  • Master's degree or PhD in a quantitative discipline (e.g., Statistics, Computer Science, Math, Engineering) or equivalent consulting experience.
  • Effective written and verbal communication skills to translate technical solutions and methodologies to stakeholders
  • Experience with data and machine learning pipeline orchestration via Dataiku (DSS 9 or 10) platform
  • Purpose

    Breakthroughs that change patients' lives ... At Pfizer we are a patient centric company, guided by our four values : courage, joy, equity and excellence.

    Our breakthrough culture lends itself to our dedication to transforming millions of lives.

    Digital Transformation Strategy

    One bold way we are achieving our purpose is through our company wide digital transformation strategy. We are leading the way in adopting new data, modelling and automated solutions to further digitize and accelerate drug discovery and development with the aim of enhancing health outcomes and the patient experience.


    We aim to create a trusting, flexible workplace culture which encourages employees to achieve work life harmony, attracts talent and enables everyone to be their best working self.

    Let’s start the conversation!

    Equal Employment Opportunity

    We believe that a diverse and inclusive workforce is crucial to building a successful business. As an employer, Pfizer is committed to celebrating this, in all its forms allowing for us to be as diverse as the patients and communities we serve.

    Together, we continue to build a culture that encourages, supports and empowers our employees.

    Information & Business Tech

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