Senior Associate - Data Science, Manufacturing Intelligence

Join our dynamic Manufacturing Intelligence and Global Automation (MIGA) team as a Senior Associate - Data Science, where you will leverage cutting-edge data science and AI technologies to drive innovation and optimize manufacturing processes. MIGA propels Pfizer Global Supply (PGS) towards Industry 4.0 capability by collaborating with manufacturing sites and Digital/IT teams in developing, implementing, and replicating high-value Manufacturing Intelligence solutions.

This role comes with the flexibility to work remotely.

Responsibilities

•    Develop and implement text analytics models to extract meaningful insights from unstructured data, facilitating improved decision-making and operational efficiency.
•    Design and deploy anomaly detection systems to identify deviations in manufacturing processes, ensuring process robustness and minimizing downtime.
•    Leverage machine learning algorithms to recommend optimization of manufacturing process parameters for  enhanced product quality and yield.
•    Collaborate with cross-functional teams, including process engineers, IT/digital specialists, and management, to integrate data-driven solutions into the manufacturing environment seamlessly.
•    Continuously monitor and refine machine learning models, ensuring their accuracy and relevance over time, and provide regular updates to key stakeholders on project progress and outcomes.
•    Perform model and code testing, validation and documentation required for GxP / non-GxP deployment of solutions.

Basic Qualifications

•    A PhD/Master’s degree in relevant engineering major, statistics, or computer science is preferred.
•    Minimum 3 years hands-on data science, machine learning work experience.
•    Strong Proficiency on Python and SQL programming, writing modularized code, hands-on with libraries like numpy, pandas, shap, scikit-learn, matplotlib, seaborn, plotly
•    Hands-on experience with Natural Language Processing (NLP), Text mining, word embedding techniques, knowledge of pre-trained networks, fine-tuning of pre-trained models, named entity recognition and text classification
•    Advance proficiency on data wrangling, pre-processing and data visualization
•    Multivariate modeling; Machine Learning; Anomaly detection techniques, deep learning frameworks like PyTorch/Tensorflow
•    Experience of developing and deploying ML solutions in AWS or similar environments, familiarity with model version control and ML pipeline
•    Track record in applying data science and machine learning methodologies to real-world data to generate insight and support decision making (not just academics/training projects).

Preferred Qualifications
•    Chemical or Bioprocess engineer/professional with understanding of unit operations and processes in Biopharmaceutical Manufacturing.
•    Experience of deploying Interpretable Machine Learning or Explainable AI and knowledge of Shapley values and plots
•    Hands-on project experience in developing and deploying GenAI solutions for Retrieval-Augmented Generation (RAG) and agentic applications.
•    Demonstrated experience of storytelling with interpretability tools usable by technical experts and non-technical stakeholders
•    Independent, self-motivated personality with excellent oral and written communication skills

  
Work Location Assignment: Remote

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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