Senior Data Science Engineer

About the Role

The Manufacturing Sciences (MS) Senior Data Science Engineer I is responsible for managing Continuous Process Verification (CPV) activities including routine evaluation, escalation of signals, cross‑functional meetings, statistical analyses, and Product Quality Reviews (APQR, YBPR). The role contributes to the technical management of GxP and non‑GxP systems (e.g. Statistica, Spotfire, SIMCA) and ensures data integrity and usability through data stewardship and engineering solutions.

Key responsibilities include modifying and maintaining Statistica work spaces (Statistica Administrator duties), managing control limits, and supporting Takeda’s digital capabilities. Applicants should have subject‑matter expertise in distributed control systems, PI historian, Statistica, Discoverant, LIMS, JMP and other multivariate process analytical tools. They should be able to identify improvement projects using advanced analytics and process knowledge, have experience in commercial manufacturing facilities, and preferably possess GxP experience.

Strong cross‑collaboration skills, data stewardship, and data engineering automation for GxP activities are essential. They may also support manufacturing investigations as a digital and statistical expert.

• Lead CPV program initiatives including APQR, PQR, YBPR and cross‑functional meetings.
• Perform statistical analyses.
• Control limits and monitoring strategy evaluation.
• Act as a subject‑matter expert (SME) for Statistical Process Control (SPC).
• Ensure data integrity, visibility, and usability through stewardship initiatives.
• Execute data science and data engineering solutions to automate GxP and non‑GxP activities to enhance operational efficiency.
• Drive and support transformative digital projects to advance Takeda’s digital culture and ways of working.
• Statistica Administrator: manage end users, develop automations, develop and maintain work spaces.
• Support MA Bio Ops end users for applicable dashboards, regulatory and RTQ data requests.
• Provide statistical analysis support.
• Support regulatory inspections including routine GMP inspection.
• Use multivariate modeling methods such as PCA/PLS, OPLS, discriminant analysis, etc., and support MA Bio Ops dashboards.
• Work with SMEs to collect and process data for use in creating models, utilizing automated tools (e.g. VBA, R/Python).
• Assess and design a phased approach in the project plan based on readiness of peripheral systems, design, and building of process models and capital/resource availability.

• Bachelor’s degree in an engineering discipline, biological sciences or business (with strong background in life‑sciences operations) with a minimum of 5 years of combined experience, or Master’s degree with 3 years of experience in production environment utilizing GMP systems for supply chain (SAP or another ERP) or manufacturing operations management such as MES.
• Sound understanding of manufacturing operations and related functions, from supply‑chain planning to product release.
• Proficiency in managing systems and platforms such as Statistica or other data‑science tools.
• Knowledge of SPC and statistical methods.
• Proven ability to write maintainable code in Python or R.
• Experience with GxP software validation, data governance and stewardship.
• Experience in data mining, machine learning, and statistical modeling.
• Some experience with large language models (LLM) in pharmaceutical applications.
• Knowledge of TIBCO Data Science / Statistica, TIBCO Spotfire, SIMCA, Discoverant, Databricks, Qlik, Tableau, Power
  
  BI, Power Automate, AWS, big‑data platforms.
• Ability to collaborate well in multifunctional teams and with personnel at all levels in the organization.
• Familiar with systems validation execution and related documentation.
• Knowledge of statistics for process monitoring.
• Strong written and verbal communication skills.
• Proficiency in Microsoft Office.
• Knowledge of GMP manufacturing processes.
• Strong analytical aptitude, will­ing to learn new technologies, regulations, and best practices.
• Good understanding of biopharmaceutical batch manufacturing, material flow, unit operations and scheduling/planning.
• Ability…