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**Job Function: **
Data Analytics & Computational Sciences
**Job Sub Function: **
Data Engineering
Job Category:
Scientific/Technology
All Job Posting Locations:
Ringaskiddy, Cork, Ireland
Job Description:
Location: Raynham, Massachusetts, United States, Loughbeg, Ringaskiddy, Ireland
DePuy Synthes is recruiting for a(n) Principal Optimization Engineer.
Please note that this role is available across multiple countries and may be posted under different requisition numbers to comply with local requirements. While you are welcome to apply to any or all of the postings, we recommend focusing on the specific country(s) that align with your preferred location(s):
- Raynham, MA, US - Requisition Number: R-071956
- Loughbeg, Ringaskiddy, Ireland - Requisition Number: R-073814
Remember, whether you apply to one or all of these requisition numbers, your applications will be considered as a single submission.
Johnson & Johnson announced plans to separate our Orthopedics business to establish a standalone orthopedics company, operating as DePuy Synthes. The process of the planned separation is anticipated to be completed within 18 to 24 months, subject to legal requirements, including consultation with works councils and other employee representative bodies, as may be required, regulatory approvals and other customary conditions and approvals. Should you accept this position, it is anticipated that, following conclusion of the transaction, you would be an employee of DePuy Synthes and your employment would be governed by DePuy Synthes employment processes, programs, policies, and benefit plans. In that case, details of any planned changes would be provided to you by DePuy Synthes at an appropriate time and subject to any necessary consultation processes.
Job Overview
As a Principal Optimization Engineer, you will lead the design and delivery of high-impact optimization and simulation capabilities. This means crafting algorithms and heuristics tailored to complex supply chain problems, piloting solutions with business partners, and scaling and deploying them across the enterprise to unlock improvements in supply chain experience, effectiveness, and efficiency. Core solution areas include end-to-end optimization, multi-echelon inventory optimization (MEIO), production planning, capacity management, network modeling, simulation, and digital twin technologies. You will report to the Director of Digital Strategy & Deployment.
In this role, you will partner closely with global supply chain leaders, in-house AI and data scientists, data engineers, and product management teams — bridging the gap between advanced analytical methods and real-world operational impact.
Key Responsibilities
Define and own the operations research strategy and solution roadmap — spanning optimization, simulation, and digital twin — to address unmet supply chain needs aligned with DePuy Synthes strategic objectives. Lead the full solution lifecycle: frame the problem, develop and validate models, pilot with business partners, then scale and deploy solutions that drive measurable improvements in supply chain experience, effectiveness, and efficiency.
Partner with supply chain business leaders across DePuy Synthes functions — including manufacturing, quality, procurement, planning, logistics, and customer experience — to identify, prioritize, and frame complex problems amenable to analytical solutions. Effectively manage communication of execution timelines and performance with customer, senior leaders, and other key stakeholders
Craft novel algorithms, heuristics, and modeling frameworks to solve high-complexity supply chain problems — including end-to-end optimization, multi-echelon inventory optimization (MEIO), network modeling, simulation, and digital twin — and own deliverables end to end.
Conduct strategic build vs. buy analysis - lead detailed financial, operational, and technical analysis to evaluate in-house vs. external development. Ability to assess strategic implications of these sourcing decisions considering factors such as cost, quality, speed-to-market, and long-term business goals.
Incorporate AI/ML techniques — including machine learning, Generative AI, and Agentic AI — where they strengthen or complement core operations research solutions, enabling more adaptive and intelligent decision-support capabilities.
Develop and monitor success metrics tied to adoption, operational impact, and realized savings — ensuring solutions deliver quantifiable business value and continue to perform at scale.
Collaborate with data scientists, data engineers, full-stack developers, and product management teams to produce sustainable, reusable solutions backed by comprehensive documentation and user training, reducing technical debt and enabling broad organizational adoption.
Drive innovation of next-generation supply chain methods, staying at the forefront of the operations research literature and translating emerging techniques into practical, deployable solutions.
Qualifications
_Education: _
- Master’s or Ph.D. (preferred) in Operations Research, Industrial Engineering, Applied Mathematics, or a related technical discipline is strongly preferred.
_Experience and Skills: _
Required:
6+ years of progressive work experience in operations research, supply chain modeling, or advanced analytics — with a track record of designing, developing, and deploying optimization and simulation solutions in complex operational environments.
Experience incubating and productionalizing new analytical capabilities, working closely with data engineers, data scientists, and technical teams from idea generation through implementation.
Deep expertise in mathematical modeling, algorithm design, and heuristic development for large-scale supply chain problems including network optimization, inventory optimization, and scheduling.
Significant hands-on experience with optimization engines such as CPLEX, Gurobi, FICO Xpress, and Lyric
Hands-on experience with discrete-event and continuous simulation platforms such as Simio, FlexSim, AnyLogic, SimPy, or Arena; familiarity with additional simulation environments is a plus.
Proficiency in one or more programming languages — Python, R, Julia, or equivalent — is required; experience building production-grade analytical solutions is a strong plus.
Strong working knowledge of AI/ML techniques — including machine learning, deep learning, Generative AI, and Agentic AI — and the ability to integrate these methods into operations research solutions where appropriate.
Strong knowledge of data science, statistical modeling, and visualization tools including decision trees, neural networks, clustering, regression, and data mining techniques.
Demonstrated expertise in supply chain modeling across planning, procurement, manufacturing, logistics, and customer fulfillment including deep understanding of supply chain fundamentals — inventory theory, BOM structures, lead times, demand planning
Experience engaging with and managing university and research institution partnerships, including co-developing methodologies and translating academic research into applied solutions, is a plus.
Demonstrated success in creative problem solving with proven ability to work cross-functionally, build partnerships, and influence change across a large, complex organization.
Strong business acumen — able to assess the most appropriate analytical approach given business requirements, constraints, and trade-offs.
Demonstrated ability to develop business cases and track business benefits, including ROI, P&L savings, cash flow impact, and other key financial metrics.
Self-starter with a hands-on approach to fast prototyping and a bias toward action in ambiguous, fast-moving environments.
Proven ability to manage and prioritize multiple competing projects and stakeholder demands in a deadline-driven environment.
Excellent written and verbal communication skills — including model documentation and analyses and demonstrated experience presenting to and influencing senior leaders.
Preferred:
Familiarity with supply chain domains within MedTech or similar industry
Familiarity with tools like Jira and Confluence
Experience at the OR/ML interface or experience applying ML/GenAI methods to enhance and improve optimization algorithms
UX/UI design experience or familiarity partnering with UX/UI designers
Familiarity with design tools such as Figma and Adobe XD
Other:
Language: English proficiency required.
Travel: Up to 15% domestic travel.
Lean Six Sigma Black Belt or equivalent preferred.
APICS certification (CPIM, CSCP) is a strong plus.
For more information on how we support the whole health of our employees throughout their wellness, career and life journey, please visit www.careers.jnj.com.
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**Required Skills: **
Preferred Skills:
Advanced Analytics, Agility Jumps, Coaching, Critical Thinking, Data Engineering, Data Governance, Data Modeling, Data Privacy Standards, Data Science, Digital Fluency, Execution Focus, Hybrid Clouds, Organizing, Presentation Design, Technical Development, Technical Writing, Technologically Savvy
The anticipated base pay range for this position is:
€70,100.00 - €121,210.00
Benefits:
In addition to base pay, we offer the following benefits*: an annual bonus with set target (% of pay) depending on pay grade / location, where the actual amount is based on the employees’ and companies’ performance of the previous calendar year, or sales commissions. Moreover, we offer vacation days, parental leave for a minimum of 12 weeks, bereavement leave, caregiver leave, volunteer leave, well-being reimbursement, programs for financial, physical and mental health. We also offer service anniversary and recognition awards, and subject to the terms of their respective plans, employees - and in some location’s eligible dependents - can participate in several insurance plans. For more information, visit Employee benefits | Supporting well-being & career growth | Johnson & Johnson Careers.
*This is for informative purposes only. Amounts and actual benefits may vary by location and are subject to change.