Data Science Intern Framingham, MA

Data Science Intern job . Framingham, MA.

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Sanofi is an innovative global healthcare company dedicated to improving people’s lives. They are seeking a highly motivated Data Science Co-op to contribute to a research project focused on developing and deploying advanced machine learning and data engineering techniques to enhance digital bioprocessing systems.

• Machine Learning (ML):
  Predictive models that help monitor and forecast critical process parameters (CPPs) and quality attributes (CQAs), driving continuous improvement in biomanufacturing. These models allow for early detection of potential process deviations and ensure that desired product qualities are maintained.
• Deep Learning (DL): DL algorithms, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs), can capture non-linear relationships in complex bioprocess data, such as time-series or spectral information, that cannot be identified with traditional methods. These insights lead to more accurate predictions and optimization of processes.
• Image Processing & Computer Vision:
  This technology is used for the analysis of visual data from bioreactors, cell cultures, and other bio-manufacturing instruments. It can assist with detecting anomalies, identifying patterns in cell growth, and ensuring the stability of cultures, all of which help in process optimization.
• Digital Twins & Soft Sensors:
  These tools simulate physical bioprocesses in real-time and predict their behavior using sensor data. By employing digital twins, you can test, monitor, and optimize bioprocesses virtually, improving decision-making capabilities and process design.
• Process Analytical Technology (PAT):
  Data science is a critical enabler of PAT, which is an industry framework aimed at ensuring quality throughout the manufacturing process. By leveraging advanced analytics and real-time monitoring, PAT can be used to develop proactive strategies that detect and control process variations, leading to improved process consistency and product quality.
• Develop, train, and validate predictive models to support decision-making processes for bioprocess control.
• Apply machine learning and deep learning techniques to large-scale bioprocess datasets, including time-series data and sensor outputs.
• Use multivariate data analysis (MVDA) techniques to analyze complex, high-dimensional datasets and extract key process insights.
• Clean, preprocess, and structure data from various sources (e.g., sensors, spectrometers, batch records).
• Assist in designing and implementing data pipelines for real-time data collection, storage, processing, and visualization on digital bioprocessing platforms.
• Collaborate with teams to integrate predictive models into bioprocess monitoring systems.
• Contribute to the development of digital twins and soft sensor frameworks that simulate bioprocess performance and provide real-time decision support.
• Develop models to predict process deviations, improve efficiency, and ensure high-quality outcomes in biologics production.
• Support automation efforts by integrating machine learning models into decision-making workflows that optimize process control and reduce variability.
• Analyze complex datasets to generate actionable insights into bioprocess performance and suggest improvements.
• Work with biologists, process engineers, and other stakeholders to interpret model outputs and translate them into experimental or process optimization recommendations.
• Develop and deploy predictive or classification models for monitoring critical process parameters (CPPs) and quality attributes (CQAs).
• Create prototypes of data integration pipelines that enable the seamless flow of real-time data into digital dashboards or simulation models.
• Contribute to scientific reports, presentations, and publications that document methodology, results, and insights gained through model development.
• Provide recommendations for data science strategies and tools that enhance biomanufacturing process control and enable smarter, faster decision-making.

Required:

• Currently enrolled and pursuing a master’s degree or PhD in Data…