Senior Associate @ Pfizer

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