By clicking the “Apply” button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda’s Privacy Notice (https://jobs.takeda.com/privacynotice) and Terms of Use (https://www.takeda.com/terms-and-conditions/) . I further attest that all information I submit in my employment application is true to the best of my knowledge. **Job Description** **"Join Our Team" at Zydus Takeda Healthcare Private Limited at Navi Mumbai** **At Zydus Takeda, excellence drives us, and innovation inspires us. Be part of a dynamic environment where your expertise ensures seamless operations and your passion makes a difference in transforming lives. Step into a rewarding career and contribute to delivering life-changing healthcare! 🚀** **Apply Now!** **Designation : Manager Manufacturing** **Qualification** : M.Tech/B.Tech - Chemical Engineering preferably from reputed institutes (ICT /IIT) **Experience** : Minimum 8 to10 years in API manufacturing Plant The incumbent will be a hands-on technical leader to drive data-enabled process understanding and control in GMP manufacturing. This role bridges process engineering and advanced analytics (MVDA/AI/ML) to improve yield, cycle time, robustness, and deviation prevention, while supporting the site’s roadmap on digital manufacturing, PAT/monitoring strategy, and continuous manufacturing (flow/process intensification). Success requires practical understanding of unit operations and shopfloor realities, and the ability to translate analytics into standard work, control strategy, and daily management routines. **Key Responsibilities:** **Process Monitoring, Variability Reduction, and MVDA (SIMCA)** + Lead MVDA workstreams using SIMCA (or equivalent): PCA/PLS modelling, batch variability analysis, golden batch definition, multivariate monitoring limits, and root-cause troubleshooting. + Establish multivariate + univariate monitoring strategies (SPC/PAT where applicable) and support investigations for excursions and deviations. + Convert insights into actionable operating recommendations and embed them into Tier 1/2/3 daily management (triggers, actions, escalation, countermeasure tracking). **AI/ML Use Cases for Manufacturing (GMP-Appropriate)** + Identify and execute AI/ML applications such as anomaly detection, early warning for deviations, batch quality prediction, yield-loss drivers, downtime and predictive maintenance. + Own the lifecycle: problem framing → data readiness → modeling → validation → deployment support → monitoring and re-training triggers. + Ensure governance and compliance: documentation, auditability, version control, and data integrity practices aligned with GMP/ALCOA+. **Digital Twin / Modelling / Simulation Enablement** + Develop and deploy fit-for-purpose models (first principles, hybrid, data-driven) for critical unit operations to accelerate optimization and scale-up. + Drive DoE-based process characterization and model validation/verification (design, execution support, analysis, and knowledge capture). + Partner with global/centre teams to develop digital twin components for prioritized processes/unit operations. **Data Foundations and Pipeline Enablement (Plant-to-Insights)** + Create and maintain practical data pipelines from plant and quality systems (DCS/PLC, historians, LIMS, MES, SAP/ERP, CMMS) to analytics environments. + Improve data contextualization, quality checks, and standard definitions (tags, batch mapping, timestamp alignment, missing data strategies). + Build reusable analysis templates, dashboards, and storyboards to support operations and leadership decisions. **Continuous Manufacturing / Flow Chemistry Support (Feasibility + Scale-up)** + Support process screening for flow/continuous suitability: mixing, heat/mass transfer, RTD, pressure drop, catalyst performance, plugging risks, scalability. + Define DoE-based development plans for continuous processes and document learnings for tech transfer readiness. + Collaborate with MSci/Engineering/EHS for hazard assessment and safe-by-design controls for intensified operations (exotherms, runaway prevention, relief strategy inputs). **Capability Building and Cross-Functional Leadership** + Coach teams on statistics, MVDA, DoE, and problem solving to build sustainable capability. + Participate in cross-site analytics communities and share best practices. **Qualifications (Desirable)** + **Education:** M.E./M.Tech in Chemical Engineering (or equivalent). + **Experience:** 8–10+ years in API or Formulations manufacturing / MSAT / MSci / process engineering roles in regulated environments. + Proven track record converting analysis into measurable manufacturing improvements (quality, yield, cycle time, reliability, deviations). **Technical Skills (Must-Have)** + **MVDA:** SIMCA (preferred) or equivalent; PCA/PLS; interpretation of multivariate control and batch variability. + **Statistics:** SPC, capability, regression, hypothesis testing, and **DoE** (design + analysis + translation to actions). + **Analytics:** Python or R (preferred) for reproducible analysis; data wrangling and time-series handling; visualization/storyboarding. + **Manufacturing systems familiarity:** historians/time-series data + linkage with LIMS/MES/SAP/CMMS; strong data contextualization ability. + **GMP & Data Integrity:** ALCOA+ mindset; documentation discipline; understanding what requires change control/validation support. **Desirable (Nice-to-Have / Differentiators)** + **Process modelling/kinetics tools:** gPROMS, DynoChem, ReactionLab **(or equivalent).** + CFD exposure: Ansys / STAR-CCM+ **(or equivalent).** + Manufacturing analytics platforms: BioVia Discoverant, PI System analytics, advanced BI tooling. + Flow chemistry/continuous manufacturing exposure (PFR/CSTR/packed-bed) and practical scale-up risk thinking. + Low-code apps/dashboards (PowerApps/Power BI) used under appropriate governance. **Behavioural Competencies** + Human-centric problem solving: designs solutions that simplify work and improve decision quality on the shopfloor. + Systems thinking: links process physics, data signals, and business outcomes. + Resilience mindset: builds monitoring and early-warning systems to prevent disruptions and support reliable supply. + Influence without authority: can drive cross-functional adoption and standardization. + High ownership, structured thinking, and the ability to manage multiple priorities independently. **What You Will Get to Do** + Build a modern, resilient manufacturing capability combining **process engineering + digital + analytics** . + Lead high-impact projects with direct visibility to site leadership and global teams. Work on advanced manufacturing themes including MVDA-led control strategies, digital twins, and continuous manufacturing enablement. **Locations** IND - Navi Mumbai **Worker Type** Employee **Worker Sub-Type** Regular **Time Type** Full time