Data Science Manager
Confirmed on the employer's own hiring board on Oct 31, 2026. First seen by Alion on Jul 31, 2026. Smith+Nephew scores B on the Alion truth index.
Life. Unlimited. At Smith+Nephew we design and manufacture technology that takes the limits off living.
Are you passionate about applying Artificial Intelligence and advanced analytics to solve complex supply chain challenges? As our Data Science Manager, you will lead the development of next generation Autonomous Planning capabilities that help transform how planning decisions are made across demand, supply and inventory management. This is a unique opportunity to combine technical expertise, business engagement and people leadership to deliver AI powered solutions that create measurable value at scale.
What will you be doing?
In this role, you will lead a Data Science Pod focused on designing, building and deploying advanced analytics, machine learning and optimisation solutions that directly influence supply chain planning decisions. Working closely with Supply Chain Planning stakeholders and the Centre of Excellence, you will help shape a portfolio of high value use cases and ensure solutions are embedded into planning systems and day to day business processes.
You will play a key role in advancing Autonomous Planning through AI powered planning engines across forecasting, inventory optimisation, replenishment planning, planning parameter optimisation and scenario modelling. Beyond model development, you will be responsible for ensuring solutions are adopted, deliver measurable outcomes and support better business decisions.
You will also help build internal capability by coaching Data Scientists, driving best practices, fostering experimentation and supporting the transition of innovative concepts into scalable production solutions.
What will you need to be successful?
Success in this role comes from combining strong technical expertise with a clear focus on business impact. You will be able to connect advanced analytics with real world planning outcomes while building strong partnerships across technical and business teams.
Key requirements include:
- Strong expertise in machine learning, time series forecasting and advanced analytics, with experience in optimisation techniques considered advantageous
- Experience delivering production ready data science solutions that influence operational and business decisions
- Strong stakeholder management skills with the ability to translate complex analytical outputs into clear and actionable recommendations
- Proficiency in Python, MLOps and modern data science platforms within enterprise data environments
- Prior experience leading, mentoring or managing a Data Science team would be nice to have, but is not essential
The anticipated base compensation range for this position is 159,500 PLN - 239,250 PLN annually.
The actual base pay offered to the successful candidate will be based on objective, job related factors including (but not limited to) relevant skills, qualifications, and experience, scope and responsibilities of the role, geographic location, and internal equity considerations. Compensation decisions are made using consistent and gender neutral criteria, in line with applicable pay transparency laws. This role has been evaluated within our internal job architecture and mapped to a defined pay band to ensure consistency and fairness.
You. Unlimited.
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Inclusion & Belonging: Committed to Welcoming, Celebrating and Thriving on Inclusion and Belonging, Learn more about our Employee Inclusion Groups on our website
Your Future: Generous annual bonus, life insurance, Save As You Earn share options.
Work/Life Balance: Flexible Vacation and Time Off, Paid Holidays and Paid Volunteering Hours, so we can give back to our communities!
Your Wellbeing: Private Health and Dental plans, multisport card/my benefit platform and much more.
Flexibility: Hybrid Working Model (For most professional roles).
Training: Hands On, Team Customised, Mentorship, subsidies for language classes, certifications and postgraduate studies
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