Senior Data Scientist (Optimisation Focus)

Elsbethen, Österreich, Vollzeit

If you're passionate about solving complex real-world problems through mathematical optimisation and want to create measurable business impact at one of the world’s most iconic brands — this role is for you.

In this position, you'll be a key contributor to global Data Science projects focused on optimising large-scale systems, including network design, supply chain planning, production scheduling, and beyond. As our in-house Optimisation Expert, you will design, build, validate, and refine mathematical models that help guide strategic and operational decisions across the business. You understand how optimisation models work under the hood, know when to apply MIP, LP, or heuristic techniques, and can translate complex business requirements into scalable models — always balancing rigor with real-world constraints. You're comfortable working with commercial solvers like Gurobi, CPLEX, or open-source tools, and know how to tune performance for production readiness.

You’re not only focused on model outputs: you know how to collaborate with business stakeholders and team members to define objectives, communicate assumptions and trade-offs, and guide decisions with clarity and confidence.

RESPONSIBILITIES

Areas that play to your strengths

All the responsibilities we'll trust you with:

DELIVER PROJECTS PART OF EXISTING DATA SCIENCE SERVICE LINES

You'll support the team by efficiently managing, running, and delivering Data Science projects with a key focus on our Operations stakeholders. This end-to-end approach includes everything from project scoping, execution, quality assurance, and delivery via convincing presentations.

STAKEHOLDER MANAGEMENT

You'll build close relationships with internal and external stakeholders. Thanks to your collaborative attitude and ability to absorb constructive feedback, you will maximise the likelihood of making each and every Data Science initiative a success for the company.

DRIVE INNOVATION

Not content focusing exclusively on existing service lines and initiatives, you will actively think along and propose new ways of generating even more value for our stakeholders.

ORGANISATIONAL RESPONSIBILITIES

You'll work inside the Data Science Team and you'll support them with impact tracking, project and pipeline planning, preparing materials for the planning cycles, internal trainings, onboarding new colleagues, internal and external outreach and more.

EXPERIENCE

Your areas of knowledge and expertise

that matter most for this role:

• 4+ years of experience in Data Science. Previous experience working on Data Science topics in Operations / Supply Chain is a plus.
• Programming: proficient in at least one of R, Python, SQL with the ability and willingness to learn the other two.
• Data Literacy: ability to prepare datasets ensuring top quality such that essence of said data and the implications for the problem at hand can be grasped quickly.
• Technical Literacy: applied understanding of modern computing allows the candidate to do things which go beyond the strict definition of Data Science (git, API calls, web crawling, …).
• Statistical Reasoning: applied understanding of Stats and Probability and know how to use these tools to reduce uncertainty in a business context (regression, visualization).
• Presentation Skills: present coherent data stories at the appropriate level of abstraction given the audience.
• Stakeholder Management: skilled at building mutually beneficial connections with functional stakeholders.
• Pragmatic Critical Thinking: intuitively consider relevant costs/benefits in all decisions and act accordingly.
• Outcome Driven: highly motivated to add value and to demonstrate that impact to the organization.
• Scientific Reasoning/ Scoping: ability to define and formulate new questions, in addition to answering given ones.
• Grit: proven capability to see things through to the end even if initial feedback is discouraging.

Travel 0-10%

JOIN THE TEAM

Got what it takes?

In your application we want to see your personal style - what makes you tick and why you think your next opportunity is here with us.