Job Description

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"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! ?
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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

Skills Required