Data Scientist – Supply Chain Optimization - Group Digital, INGKA Group

About this job

Location options: Visa sponsor, Paid relocation
Job type: Full-time
Experience level: Junior, Mid-Level, Senior
Role: Data Scientist
Industry: Cloud-Based Solutions, Data & Analytics, eCommerce
Company size: 10k+ people
Company type: Private

Technologies

git, python, machine-learning, google-cloud-platform

Job description

WHO YOU ARE

We are looking for a number of data scientists to join a group focused on improving our supply chain, through the use of optimization and machine learning. We would love to talk with you, if you:

• Absolutely love figuring out how to use math, code and data to solve business problems
• Have a strong background in Math, Operations Research, Computer Science (PhD or a few years relevant experience is a plus)
• Have experience building decision support tools, ideally for supply chain problems
• Can code well, preferably with experience beyond basic notebooks or scripts (we mainly use Python)
• Have experience with optimization solvers, e.g. Gurobi or similar
• Are a team player who takes ownership, and likes to work closely with other people
• Listen well, and can explain your ideas to stakeholders
• Are curious and like to learn continuously

Note that this is our wish list and it’s not sorted in a particular order. You might still be a good candidate for the role even if you don’t recognize yourself in all of these points. We like to think long term and invest in people’s development.

The IKEA culture and values are very much a part of our business and day to day work life. For you to thrive and grow with IKEA it’s important for us that you share our values! You can read more regarding our values and life at IKEA on our website http://www.ikea.com

WHAT YOU'LL BE DOING DAY TO DAY

The way IKEA delivers to customers is undergoing radical changes and our group is supporting that change. For example, we are building models and tools that help to:

• Determine the best way to deliver online orders to each customer.
• Improve the efficiency of warehouse operations, such as order picking.
• Increase the capacity utilization of our transport providers.
• Optimize how we store and replenish our products.

You will work in a cross-disciplinary agile team that designs, implements and deploys models that help to solve these kinds of problems. It will be a mix of mathematical modeling, training machine learning models and writing code – as well as talking with product owners and business stakeholders.

OUR TEAM WITHIN IKEA

IKEA has long been a global leader in home furnishing. We are proud of our vision to improve the everyday life of the many people. But our industry is quickly changing and we need to adapt to stay competitive. As part of IKEA’s journey to strengthen our digital capabilities, we are building a Data & Analytics function with a new Data Science team. This team is working on problems across the company, from customer modeling to logistics optimization. We see so many opportunities for what we can accomplish and have an ambition to become a world class team. At the same time, we believe that our work is not just about building models, but also about learning and having fun together.

We can offer you:

• Work on some very interesting problems in our supply chain
• Opportunities to have global impact with your work
• Flexible and modern tools: We deploy on Google Cloud Platform, we use a lot of open source tools, and Gurobi for optimization models
• Hardware of your choice (Mac or Windows)
• A team of great colleagues to learn with and from (including several PhD’s in Applied Math and Operations research)
• Flexible and friendly working environment
• Relocation support (we are based in south Sweden)
• Continuous learning (we aim to spend 20% of our working time on learning)

QUESTIONS AND SUPPORT? LET'S CONNECT!

For more information about the role, please contact Erik Eng, Data Science Chapter Lead, at [email protected]. If you have any questions regarding the recruitment process, please contact [email protected]