Data Scientist

at  IKEA

WHO YOU ARE

We are looking for a Data Scientist to join us in developing ways for IKEA to stay relevant for our customers. We are using data and analytics within cross-functional teams, to create value all along our customer’s journey.

Our diverse Data & Analytics team in Customer Engagement is growing and we would love to talk with you, if you recognize yourself in some of the following:

• passionate about understanding a business problem and applying Data & Analytics to try and solve

them

• have experience in developing data and statistics-driven solutions for real-life business problems
• exhibit the ability to clearly communicate statistical and machine learning concepts to non-technical

stakeholders, ensuring a shared understanding of the models’ impact and operational requirements.

• demonstrate proficiency in deploying and maintaining robust machine learning models in production

environments, ensuring their performance and reliability.

• master techniques for Data Science and can choose relevant algorithms fit for purpose, such as

gradient boosting, Bayesian modelling, deep learning, natural language processing, time-series

analysis or optimization/OR techniques

• have experience leading the development of advanced analytics frameworks within large

organizations

• are a team player who takes ownership, builds cross-functional relationships with senior peers and

loves sharing knowledge with other Data Scientists and coworkers

• are curious, self-directed and want to keep learning!

This is our wish list! If you don’t recognize yourself in all these points, you might still be an excellent candidate for the role. We like to think long-term and invest in people’s development together with us.
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.

IKEA is taking huge steps in its digital transformation and our Data & Analytics Customer team is at the forefront of building intelligent systems for data-driven business decisions. For example, within Customer Engagement we are developing models and tools to answer questions like:

• How do we best encourage our customers to log-in to have a more seamless journey on the web and

app?

• How can we ensure that we send the most relevant content at the right time to our customers?