Decision Analytics Consultant – Process Engineer; Manufacturing

Overview

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 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 engagement. We partner 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.

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, quality-driven tradeoffs, balancing throughput, risk, and compliance in a cGMP environment.
• Work with analytics and digital teams to leverage data from MES, historians, LIMS, QMS, SAP, and other systems to track KPIs (e.g., OEE, yield, cycle time, quality metrics) and identify improvement opportunities.
• Contribute to thought leadership and practice development in areas such as process optimization, tech transfer, scale-up, and smart manufacturing within life sciences.
• Support and sometimes lead client presentations, workshops, and design reviews, clearly communicating technical concepts and trade-offs to both technical and business stakeholders.
• Collaborate with ZS colleagues to define project scope, develop workplans, and ensure on-time, high-quality delivery across multiple engagements.
• Mentor junior team members, provide feedback, and help build functional expertise within the broader manufacturing and operations team.

• Bachelor’s degree in Engineering (e.g., Chemical, Biochemical, Mechanical, Industrial) or a closely related technical discipline; an advanced degree is a plus.
• 5+ years of relevant experience in process engineering or technical consulting within the pharmaceutical, biotech, or broader process industries, with exposure to large-scale biologics, cell & gene therapy, or aseptic manufacturing.
• Demonstrated experience in process design and improvement, such as:
• Designing or modifying unit operations (upstream, downstream, utilities, or fill–finish)
• Conducting capacity and throughput analyses
• Improving safety, quality, and reliability through engineering changes
• Supporting tech transfer or scale-up activities
• Comfort analyzing and synthesizing large data sets, developing clear visuals, and translating insights into actionable recommendations for clients.
• Strong understanding of Quality systems that are part of…