Senior Data Scientist -Manufacturing

Role Overview:

Core Responsibilities

• Analyze and interpret large-scale EBR and manufacturing datasets to identify trends, anomalies, and opportunities for process improvement and risk mitigation.
• Develop and deploy advanced statistical models and machine learning algorithms to predict batch quality outcomes, detect deviations, and optimize production workflows.
• Ensure data integrity and compliance by working closely with quality and regulatory teams to maintain audit trails, electronic signatures, and documentation standards as per cGMP requirements.
• Integrate EBR data with other enterprise systems such as MES, LIMS, and ERP to create unified data models supporting end-to-end manufacturing analytics.
• Collaborate with IT and software developers to implement data pipelines, dashboards, and visualization tools that provide real-time insights to manufacturing and quality stakeholders.
• Lead efforts in digital transformation projects aligned with Pharma 4.0, including automation, real-time monitoring, and advanced analytics.
• Communicate complex analytical findings effectively to both technical and non-technical stakeholders to drive data-driven decision-making.
• Participate in validation and qualification activities for analytics solutions to ensure compliance with regulatory standards.
• Provide training and support to manufacturing teams to facilitate adoption of analytics tools and foster a data-driven culture.

Required Skills and Experience

• Strong statistical and mathematical background with expertise in data mining, predictive modeling, and causal analysis.
• Hands-on experience with pharmaceutical manufacturing data, especially Electronic Batch Records (EBR), and understanding of batch production processes.
• Knowledge of regulatory compliance requirements related to data integrity, cGMP, and audit readiness in pharma manufacturing.
• Proficiency in programming languages such as Python and/or R for data analysis, modeling, and automation.
• Experience with cloud platforms (e.g., AWS) and big data technologies for scalable analytics solutions.
• Familiarity with integrating and analyzing structured and unstructured data from MES, LIMS, ERP, and EBR systems.
• Ability to manage complex data integration challenges and maintain secure, compliant data environments.
• Excellent problem-solving skills and ability to work collaboratively across geographies and functions.
• Prior experience in pharma or biotech industry analytics roles, preferably involving Medical Affairs or manufacturing data analytics.
• Knowledge of natural language processing (NLP) and advanced visual analytics is a plus.

Preferred Qualifications

• 4+ years of advanced analytics experience, including machine learning and statistical modeling.
• 7+ years of experience with a strong focus on pharmaceutical data science.
• Experience in causal inference, AI/ML applications, and predictive modeling in pharma contexts.
• Familiarity with electronic signature systems, digital audit trails, and EBR software platforms.
• Strong communication skills to translate analytics into business insights and influence decision-making.