WHO YOU ARE
We are looking for a number of data scientists to join a group working on pricing across Ikea. We focus on developing cutting edge tooling in all areas of pricing, to ensure the best experience for our customers, as well as our co-workers. To do that, we are looking to building a diverse team consisting of talented data scientists,
We would love to talk with you, if you:
- love getting to understand business problems through data,
- have a strong background in a highly mathematical subject,
- have experience developing mathematical solutions to real-life business problems,
- enjoy being creative through code – Python is our main language, but deep experience with other stats and data processing languages is great,
- have experience working with pricing, ideally in a retail company,
- are a great communicator with technical stakeholders, business stakeholders and data science peers,
- want to keep learning!
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 www.ikea.com.
WHAT YOU'LL BE DOING DAY TO DAY
IKEA is taking huge steps to become a data-driven company in all aspects. Pricing is a key focus area in this transition. It is a highly strategic part of the business with a high potential value, where we are looking to revamp our existing tools, and as well as address new areas. This includes pricing of furniture, food and services across all parts of the product life cycle.
We want you to help us build ML software to answer questions like:
- How should we price our range to ensure our furniture is accessible for the many people no matter where they?
- How do we increase demand of outgoing items to make space for news?
- Delivery is complex – how do we set prices to ensure best customer experience?
- Can we use intelligent pricing to drive sustainability and circular economy?
- What can we learn about fashion and trends to inform price-setting on new items?
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 pricing to forecasting. 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 pricing, and you are encouraged to spot opportunities to collaborate with data science colleagues in other specialist teams.
- Opportunities to have global impact with your work.
- Flexible and modern tools: We deploy on Google Cloud Platform and we use a lot of open source tools across the board.
- Hardware of your choice.
- A team of great colleagues to learn with and from.
- Continuous learning (we aim to spend 20% of our working time on learning).
- Flexible and friendly working environment.
- Relocation support: we are based in southern Sweden.
QUESTIONS AND SUPPORT? LET'S CONNECT!
Does this sound like your next challenge? IKEA offers an exciting and empowering work environment in a global workplace. And as the world’s leader at life at home, you have exceptional opportunities to grow and develop together with us.
Please apply with your application in English. Please not that we can´t process any applications through email. Thank you.