Saad LAHKIM

As a Data Scientist at Sanofi for the SPC Booster project, I am responsible for optimizing the production yields of vaccine manufacturing facilities. My key tasks include: - Data Preparation : Cleaning, merging, and structuring data in Dataiku for reliable analysis. - Statistical Analysis : Identifying trends and key factors through exploratory and multivariate analyses. - ML Modeling : Developed ML models that improved vaccine yields by 6–10\%, translating into substantial cost savings due to the scale of pharmaceutical manufacturing. - Discrete Data Extraction : Automatically identifying phases and key points via smoothing and mathematical analysis. - Method Standardization : Implementing a generic and reusable modeling procedure for all future SPC Booster projects. - Interdisciplinary Collaboration : Aligning analyses with industrial constraints in collaboration with bioengineers and process experts.

- Gesture Recognition on Humanoid Robot : Training the NAO robot to recognize hand gestures using machine learning and transfer learning, achieving a theoretical accuracy of 84% on both synthetic and real data. - Human-Robot Interaction : Developing a model that enables NAO to interact with users, particularly children, through games such as Rock-Paper-Scissors. - Computer Vision Research : Studying advanced machine learning techniques for craniofacial reconstruction, peripheral nerve surgery, and breast reconstruction, under the supervision of Dr. Khan Iftekharuddin. - Demonstration and Outreach : Co-leading an AI workshop at the Slover Library (Norfolk), where NAO achieved an accuracy of 80% in real-world interaction conditions.

- Monitoring and Reporting : Developing SPLUNK alerts and dashboards used daily by the BI team to monitor DataStage and Power BI jobs. - Analysis and Optimization : Analyzing logs to detect real-time anomalies and intervening promptly to avoid interruption costs. - Workflow Migration : Conducting pilot tests for the transition from DataStage to SSIS.