Job Introduction

Handelsbanken combines a long-established relationship banking model with secure, resilient, and customer-focused technology. Our technology teams enable the Bank's decentralised way of working, delivering systems built for stability, trust, and long-term value.

We are on a multi-year technology and digital transformation journey to enhance customer experience and improve how colleagues work together. By modernising platforms, simplifying processes, and better connecting data and systems, we help relationship teams focus on customers and less on complexity.

Our decentralised culture extends to technology. Teams are trusted to take ownership, make informed decisions, and deliver sustainable, high-quality solutions. We value engineering excellence, pragmatic problem-solving, and strong collaboration across technology, business, and risk.

We offer technologists the opportunity to build lasting careers, deepen their expertise, and contribute to meaningful change. We look for people who care about quality, security, long-term impact, and who want to shape the future of a relationship-led bank.

Check our Handelsbanken website for further information

The opportunity

As part of a broader multi-year change initiative, we are looking to appoint an experienced Lead Data Scientist within our Efficiency and Automation team.

You will be responsible for defining our data science strategy in collaboration with the Head of Data architecture, and Head of Data platforms to deliver the bank wide data and AI roadmap, platform strategy and best practices. This will include ensuring that the data strategy and corresponding technology choices enable the bank's AI ambitions in the analytics space

Key responsibilities

• Define and lead the data science strategy, feeding into the banks data and platform strategy.
• Leadership of data scientists within a cross functional team.
• Working with large and complex datasets to develop, test and deploy machine learning and AI models into production environments.
• Using MLOps practices to support model deployment, monitoring, governance, and continuous improvement.
• Evaluating emerging technologies and analytical techniques to identify opportunities for innovation and business value.
• Ensuring models and analytical solutions meet regulatory, governance, and risk management standards within a financial services environment.
• Reinforce Agile ways of working, using pair programming, DORA insights and best practices to help to foster an environment of continuous improvement within the team

What we're looking for

Research (by Harvard University) shows that women are particularly likely to second guess themselves and not apply - so if you are worried you don't meet all the criteria, get in touch anyhow and let us do the worrying...

• Experience in leading and design of enterprise wide data science strategy within financial services or similarly regulated industry.
• Experience working with modern data platforms, software engineering best practices, and data science tooling to develop scalable and maintainable analytical solutions.
• Strong communication skills, with the ability to explain complex technical concepts and analytical findings to both technical and non-technical audiences.
• Strong practical knowledge of statistics, mathematics, and machine learning techniques, with experience developing, validating, deploying, and monitoring predictive and analytical models in production environments.
• Advanced Python and SQL skills, with experience using tools such as Jupyter/JupyterHub to conduct data exploration, develop machine learning solutions, and support production workflows.
• Hands-on experience applying machine learning techniques using frameworks such as XGBoost, PyTorch, or similar technologies to solve complex business problems and deliver measurable value.
• Experience translating business requirements into actionable analytical solutions, working closely with stakeholders to identify opportunities, define approaches, and deliver data-driven outcomes.
• Experience with Large Language Models (LLMs), Generative AI, Retrieval-Augmented Generation (RAG), or other emerging AI technologies.

Why join Handelsbanken

We want everyone at Handelsbanken to feel supported, motivated, and able to do great work. That's why, alongside brilliant colleagues, meaningful work and training and development opportunities, we provide a variety of benefits designed with your wellbeing in mind.

In addition, there is a flexible benefits package with the key highlights detailed below.

Application next steps

Your journey with us begins once you have submitted your application. One of our Handelsbanken Talent Acquisition Partners will be reviewing your details and will later organise a phone conversation if your experience aligns with our requirements, we will extend an invitation for you to participate in an interview.

This advert will be live for a minimum of two weeks. However, please note that after the two weeks, the closing date could change at any time depending on the number of responses received.

The Bank is deeply committed to embedding good equality and diversity practice into all of our activities. This is so that we are an inclusive, welcoming and inspiring place to work that encourages everyone to apply, regardless of socio-economic background, age, disability, pregnancy and/or parental status, race (including colour, nationality, and ethnic or national origin), veteran status, marital and civil partnership status, religion or belief, sex, gender reassignment or sexual orientation.

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