WHAT YOU’LL DO
As a Senior Data Scientist, you will work hands on to solve complex business and product problems using data and machine learning. You will collaborate closely with cross functional teams and be expected to work pragmatically, navigate ambiguity, and focus on delivering measurable impact.
- Own and contribute to data science initiatives end to end, from understanding problem statements and exploring data to building, deploying, and maintaining models in production.
- Design, deploy, and operate LLM‑powered tools and workflows in production, with responsibility for evaluation, monitoring, and continuous improvement
- Apply statistical methods, machine learning, and advanced analytics to support product and business decisions.
- Develop, test, and improve models and data‑driven solutions with a strong focus on quality, scalability, and long‑term maintainability.
- Take responsibility for solutions after deployment, including monitoring, troubleshooting, and iterative improvements.
- Perform exploratory and ad hoc data analysis, and present insights in a clear and structured way.
- Communicate closely with stakeholders to translate business needs into analytical approaches and explain outcomes in an accessible manner.
- Contribute to technical standards, best practices, and knowledge sharing within the data science community.
WHO YOU’LL WORK WITH
You will work in cross‑functional teams together with colleagues in product, engineering, analytics, and business roles. You will also be part of a broader Data Science community, collaborating with other data scientists to share knowledge, align on best practices, and continuously improve how data science is applied across the organisation.
WHO YOU ARE
We are looking for people with…
- A Bachelor’s or Master’s degree in Statistics, Engineering, Computer Science, or a related field.
- Strong theoretical and practical knowledge of statistics and machine learning.
- Proven experience developing and deploying machine learning models in cloud environments beyond notebook‑based work.
- Hands‑on experience building and deploying LLM‑based applications, including fine‑tuning, retrieval pipelines, and prompt engineering.
- Strong proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, LangChain, or similar libraries.
- Practical experience with MLOps practices, CI/CD pipelines, and model monitoring, ideally in a cloud environment.
And people who are…
- Strong in their SQL skills for data manipulation and analysis
- Familiar with DBT or similar data transformation tools
- Experienced with vector databases and embedding models
- Excellent communicators and confident taking ownership and accountability
- Comfortable working in ambiguity while being proactive
Please note that we will not be able to offer relocation for this role, so we will not be able to proceed with candidates living/working outside of Sweden.
WHO WE ARE
H&M Group is a global company of strong fashion brands and ventures. Our goal is to prove that there is no compromise between exceptional design, affordable prices, and sustainable solutions. We want to liberate fashion for the many, and our customers are at the heart of every decision we make.
We are made up of thousands of passionate and talented colleagues united by our shared culture and values. Together, we want to use our power, our scale, and our knowledge to push the fashion industry towards a more inclusive and sustainable future.
WHY YOU’LL LOVE WORKING HERE
At H&M Group, we are proud to be a vibrant and welcoming company. We offer our employees attractive benefits with extensive development opportunities around the globe.
- We offer all our employee’s attractive benefits with extensive development opportunities around the globe. All our employees receive a 25% staff discount usable on all our H&M Group brands in stores and online. In addition to our staff discount, all our employees are included in our H&M Incentive Program – HIP. You can read more about our H&M Incentive Program here.
- 30 days holiday
- We offer a collective agreement which includes pension and life insurance
- H&M Incentive Program
- Wellness benefit 4000kr/year (from Jan 1, 2026)
- Benify Benefits Portal
- Community with activities
JOIN US
Our uniqueness comes from a combination of many things – our inclusive and collaborative culture, our strong values, and opportunities for growth. But most of all, it’s our people who make us who we are.
Take the next step in your career together with us. The journey starts here.
*We are committed to a recruitment process that is fair, equitable, and based on competency. We therefore kindly ask you to not attach a cover letter in your application.
Skills Required
- Bachelor's or Master's degree in Statistics, Engineering, Computer Science, or related field
- Strong theoretical and practical knowledge of statistics and machine learning
- Proven experience developing and deploying machine learning models in cloud environments beyond notebook-based work
- Hands-on experience building and deploying LLM-based applications, including fine-tuning, retrieval pipelines, and prompt engineering
- Strong proficiency in Python
- Proficiency with ML frameworks such as PyTorch, TensorFlow, LangChain, or similar
- Practical experience with MLOps practices, CI/CD pipelines, and model monitoring
- Strong SQL skills for data manipulation and analysis
- Familiarity with DBT or similar data transformation tools
- Experience with vector databases and embedding models
- Excellent communication skills and ability to take ownership and work in ambiguity
H&M Group Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about H&M Group and has not been reviewed or approved by H&M Group.
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Healthcare Strength — Medical, pharmacy and vision options with low employee costs and free dental are available, alongside telehealth and inclusive offerings such as transgender, bariatric and fertility coverage. These features are highlighted as solid for U.S. retail roles, with some availability for part‑time positions depending on eligibility.
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Leave & Time Off Breadth — Vacation, flexible wellness days, company‑paid holidays and a paid birthday off are offered, with some paid time off available to part‑time staff. The time‑off structure is presented as generous within the retail context.
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Parental & Family Support — Eight weeks of paid parental pay for mothers and fathers is provided, complemented by adoption assistance and healthy pregnancy/babies programs. These family supports add depth to the core medical coverage in the U.S. package.
H&M Group Insights
What We Do
Founded in 1947, H&M Group is a global design company with ~4,702 stores in 76 markets and 56 online markets. At H&M Group, we believe in making great design available to everyone. It’s essential in everything we do. Our family of brands and business ventures offer customers around the world a wealth of fashion, beauty, accessories and homeware, as well as modern menus with fresh and local produce at some of the brands’ in-store eateries. But design is so much more than just products; it’s about clever design processes, efficient product flows, creating experiences that enrich, and smart solutions that benefit all our customers. Sustainability is always at the core of our business. Not only because we like to do what’s right — but it’s also beneficial for our business. We will continue to push for change and lead the way towards a more inclusive and sustainable fashion future. Do you want to join us? We will trust you with great responsibility right from the start, reward a passionate mindset and encourage an entrepreneurial spirit. When you start a career with H&M Group, there’s no limit to where it can take you. H&M Group's Moderation Policy: Welcome to H&M Group’s official LinkedIn page. Ask questions, exchange ideas and meet members and employees from all over the world. This page is moderated daily and we always do our best to answer each one of you in a timely manner. Please remember to keep a friendly tone and in line with LinkedIn’s legal terms at https://www.linkedin.com/legal/user-agreement Comments and posts that contain foul language, are off-topic or unnecessarily rude will be deleted. We also encourage you to report any inappropriate content. We use an external tool to handle the comments on our page, so please note that your comments can be stored. For questions, please contact our team at [email protected].
