Básico
Data Scientist
Publicado: 22.05.2026
Data de encerramento: 06.07.2026
Referência de emprego: 11bfbc71e231bcbeacd5ab2cd43e4d2f
Informação do emprego
Localização
Malmö, null, Sweden
Empresa
TN Sweden
Cliente / Empregador
Ikea
Referência de emprego
11bfbc71e231bcbeacd5ab2cd43e4d2f
Tipo de listagem
Básico
É necessária autorização de trabalho da UE
Não
Publicado
22.05.2026
Data de encerramento
06.07.2026
Descrição do cargo
Job ID: Date posted: 10/06/ 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 customers 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 dont 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 peoples 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 its important for us that you share our values! You can read more regarding our values and life at IKEA on our website What you'll be doing day to day 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? Our team within Ikea You will work in Data & Analytics together with other Data Analysts, Data Scientists and Data Engineers. Together you will be joining cross-functional teams consisting of colleagues from Technology, Product and Design, that design, implement and deploy products that help to solve these kinds of problems. It will be a mix of product insights, data visualization and writing code as well as talking with product owners and business stakeholders. 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 IKEAs journey to strengthen our digital capabilities, we are building a Data & Analytics function. This team is working on problems across the company, ranging from customer modeling, loyalty, customer communication and more. We see so many opportunities for what we can accomplish and have the ambition to be 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 as described above, and you are encouraged to spot new opportunities or 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 and OS of your choice. A team of great colleagues to learn with and from (with world-class experience across all aspects of Data Science). Continuous learning (we aim to spend 20% of our working time on learning). Flexible and friendly working environment. Relocation support (If Senior) if not already in the area: we are based in southern Sweden, Amsterdam in the Netherlands, and in Madrid, Spain. 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 worlds leader at life at home, you have exceptional opportunities to grow and develop together with us. If you have questions regarding the recruitment system, please reach out to Annette Björkquist-Åhstedt at . Please apply with your application in English. Note that we cant process any applications through email. As you might know, in Sweden its common to take a few weeks of holiday during July, most people take over multiple weeks in a row; at IKEA we are no different. We believe in a healthy work-life balance and encourage our co-workers to take time to relax, recharge, and unwind. Because of this great benefit, we might take a bit longer to get back to you, we will return in August, and you should hear from us as soon as possible. We look forward to learning more about you! Thank you!
Competências
apply blended learning
apply for research funding
apply research ethics and scientific integrity principles in research activities
build recommender systems
Business Analytics
Business Intelligence
collect ICT data
communicate with a non-scientific audience
Computational Biology
Computer Simulation
conduct research across disciplines
create data models
Data Engineering
data ethics
Data Mining
Data Models
data quality assessment
Data Science
data visualisation software
define data quality criteria
deliver visual presentation of data
demonstrate disciplinary expertise
design database in the cloud
design database scheme
develop data processing applications
develop professional network with researchers and scientists
Digital Curation
disseminate results to the scientific community
draft scientific or academic papers and technical documentation
empirical analysis
establish data processes
evaluate research activities
execute analytical mathematical calculations
Hadoop
handle data samples
Healthcare Analytics
image recognition
implement data quality processes
increase the impact of science on policy and society
information categorisation
Information Extraction
integrate gender dimension in research
integrate ICT data
interact professionally in research and professional environments
interpret current data
LDAP
LINQ
make data-driven decisions
manage data
manage data collection systems
manage findable accessible interoperable and reusable data
manage ICT data architecture
manage ICT data classification
manage intellectual property rights
manage open publications
manage personal professional development
manage research data
Marketing Analytics
mathematical modelling
MDX
mentor individuals
multidisciplinary research
N1QL
normalise data
online analytical processing
operate open source software
perform data cleansing
perform data mining
perform project management
perform scientific research
promote open innovation in research
promote the participation of citizens in scientific and research activities
promote the transfer of knowledge
publish academic research
quantitative analysis
query languages
report analysis results
Research Design
resource description framework query language
Scientific Computing
scientific literature
Social Network Analysis
SPARQL
speak different languages
State Estimation
statistical modeling techniques
Statistics
synthesise information
teach in academic or vocational contexts
think abstractly
Unstructured Data
use data processing techniques
use databases
use spreadsheets software
visual presentation techniques
write scientific publications
XQuery