Decision Analytics Consultant – Process Engineer (Manufacturing)

ZS is a place where passion changes lives

As a management consulting and technology firm focused on improving life and how we live it, we transform ideas into impact by bringing together data, science, technology and human ingenuity to deliver better outcomes for all

Here you’ll work side-by-side with a powerful collective of thinkers and experts shaping life-changing solutions for patients, caregivers and consumers, worldwide

ZSers drive impact by bringing a client-first mentality to each and every engagement

We partner collaboratively with our clients to develop custom solutions and technology products that create value and deliver company results across critical areas of their business

Bring your curiosity for learning, bold ideas, courage and passion to drive life-changing impact to ZS.

 

Insights & Analytics 

ZS’s Insights & Analytics group partners with healthcare and life sciences clients to solve complex manufacturing and operations challenges using data, engineering rigor, and structured problem solving.  

We are seeking a Process Engineer Consultant (Decision Analytics) with strong domain expertise in commercial pharmaceutical manufacturing and shopfloor experience who have worked closely with manufacturing operations and quality systems. They will support and lead projects focused on designing, optimizing, and scaling pharmaceutical and biotech manufacturing processes. 

This role is ideal for an engineer with hands-on experience in one or more of biologics, cell & gene therapy, or aseptic/sterile fill–finish operations, who enjoys working cross-functionally and using data to improve safety, efficiency, and product quality.  

 

What You’ll Do: As a Decision Analytics Consultant in Manufacturing, you will...

• Lead and support process design, operational improvement and optimization projects across drug substance and drug product manufacturing (e.g., upstream, downstream, utilities, fill–finish), from early concept through detailed design and implementation. 

• Partner with client engineering, manufacturing, quality, and supply chain teams to map current processes, identify bottlenecks and recurring issues, and propose innovative design and operating strategies that improve throughput, safety, maintainability, and flexibility for future products. 

• Use (manufacturing and quality) data-driven analysis (e.g., equipment performance data, production data, deviation trends) to diagnose process issues, quantify impact, and recommend short- and long-term solutions.  

• Contribute to facility and equipment design for new or expanded manufacturing capacity, including process flow development, material and personnel flows, and support for multi-product or “lights-out” / high-automation concepts where appropriate. 

• Link manufacturing performance improvements (e.g., OEE, yield, cycle time) to broader supply chain outcomes such as service levels, reliability, and supply assurance. 

• Support deviation investigations, change control discussions,