Senior Data Scientist

Role Summary

Senior Data Scientist responsible for developing, maintaining, and deploying first principles and/or machine learning models for biopharmaceutical processes, including cell culture, biologics formulation development, and fill/finish processes. Lead model design, select underlying technologies and infrastructure, and ensure successful application of models in Process Development. Work with cross-functional teams and communicate technical foundations of models for engineers and scientists.

Responsibilities

• Design, develop, and deploy first principles, machine learning, and hybrid models to optimize biopharmaceutical processes.
• Integrate modeling software with real-time equipment data to enable digital twins for improved process performance and understanding.
• Build and maintain robust data pipelines and agentic workflows to streamline generation of impact-level insights.
• Collaborate with cross-functional teams to translate scientific challenges into data-driven solutions and ensure seamless model integration into process development workflows.
• Champion software development best practices, including version control, testing, and continuous integration to ensure model reliability, scalability, and reproducibility.

Qualifications

• Required: High school diploma / GED with 10 years of Data Sciences experience OR Associate’s degree with 8 years of Data Sciences experience OR Bachelor’s degree with 4 years of Data Sciences experience OR Master’s degree with 2 years of Data Sciences experience OR Doctorate degree.
• Preferred: Ph.D. in Chemical Engineering, Mechanical Engineering, Applied Math, or related field; strong background in mechanistic modeling and first principles; experience applying AI/ML algorithms to engineering problems; track record of leading modeling and data science projects; 3+ years coding experience in Python; understanding of biopharmaceutical processes and unit operations; experience using Git; familiarity with DevOps and software best practices; experience with data engineering & visualization tools (e.g., Databricks, Spotfire) and cloud computing (AWS); experience leveraging AI tools for scientific workflows; independent, self-motivated, organized, and able to multi-task in time-sensitive environments; excellent written and verbal communication; strong analytical skills.

Education

• Doctorate degree (preferred); Ph.D. in Chemical Engineering, Mechanical Engineering, Applied Math, or related field.

Skills

• Python programming (3+ years)
• Git version control
• Data engineering & visualization tools (e.g., Databricks, Spotfire)
• Cloud computing and data storage (AWS)
• DevOps practices (CI/CD, test-driven development)
• Machine learning, first-principles modeling, and hybrid modeling
• Strong communication and collaboration across cross-functional teams