Lead Data Scientist

Twoday is one of the leading digital transformation partners in Northern Europe with a global presence. With approximately 3,000 technologists, we collaborate with the most admired private and public organizations to deliver cutting-edge digital solutions. Our deep industry expertise includes Data & AI, software development, digital experiences, and business applications. Operating across the Nordics and Lithuania, our team serves over 8,000 customers and supporting their digital transformation journeys. 

We are looking for an experienced Lead Data Scientist to join our AI team!

Most organizations have no shortage of ideas for what to model. Far fewer can turn a vaguely stated business problem into a well-posed prediction task, pick the algorithmic approach that fits it, and defend the result when someone asks how the number was produced. That gap is where you come in. You will lead the analytical work that turns a customer's business problem into a model that holds up, and then into something they actually use, alongside data engineers, AI/ML engineers, cloud architects, and software developers on some of the largest Data & AI teams in the Nordics.

You will set the analytical direction on our most demanding engagements, and you will grow the people who deliver them.

What are we looking for?

You are a scientist and a builder. Given a business problem stated in a customer's own words, you can work out what should be predicted, at what granularity, against which target, with what horizon, and what a good result would even look like. You are rigorous about how you validate a result, and you have seen enough projects to have opinions about which problems are worth modelling at all and which should be solved another way.

We expect you to bring:

• Several years of hands-on data science experience, including a number of models you have taken past the prototype stage and to production.

• Proven strength in translating a business objective into a formal AI/ML problem: defining the target variable and unit of analysis, agreeing what success means with the people who will use the model, and saying early when the data will not support the question.

• Deep predictive modelling craft: classification, regression, time series and generative AI, and the ability to set the modelling standard for others.

• Judgement about algorithmic choice: when a well-specified baseline or classical statistical model is enough, when a heavier method earns its cost, and when the problem is not a prediction problem at all.

• Solid applied statistics: honest validation, uncertainty, and the ability to explain what a result does and does not support.

• Strong software fundamentals to write code others can build on.

• Experience on Azure: Azure Machine Learning, Databricks, or Microsoft Fabric (Experience from AWS or GCP transfers, and we will not hold it against you.)

• Experience applying generative AI where it genuinely fits, including RAG architectures and the evaluation of prompts and models.

• An understanding of what governance means in practice: reproducibility, model documentation, GDPR, bias and fairness considerations, and the documentation the EU AI Act increasingly requires.

• The ability to explain a technical trade-off to a customer's business stakeholder without flattening it into a slogan, and to push back when the question being asked is not the question that matters.

• Leadership shown through analytical direction, mentoring, and raising the standard of the work around you.

• Fluent spoken and written Danish is a requirement.

Will your responsibilities be?

• Lead the analytical design of AI and ML solutions for our customers, from problem framing and feasibility through to a validated, documented model in production.

• Run framing sessions with customers: shape the business problem into a prediction task with a defined target, a defined decision it supports, and success criteria the business recognises, and write down the assumptions the solution rests on.

• Own the algorithmic approach: baselines, method selection and the reasoning behind it, validation strategy, and the honest assessment of what the model is worth.

• Set analytical standards for the team: reproducibility, experiment tracking, documentation, and review of each other's work.

• Work directly with customers: shape the approach, challenge requirements when they need challenging, and translate between business outcomes and what the data can support.

• Mentor data scientists, and grow the data science capability across our Danish teams.

• Take part in scoping and pre-sales for AI initiatives, where your judgement on feasibility and data readiness carries real weight.

• Keep us current: evaluate new methods and tooling with a clear eye for what actually earns a place in customer delivery.

• Engage as an local ambassador and expert in our global AI/ML offerings

About you

• You take ownership and are comfortable working in complex environments

• You are pragmatic and focus on delivering real-world value

• You enjoy working across disciplines and bridging gaps within teams

• You lift the people around you, colleagues and the customer's own specialists, and you leave a team more capable than you found it
  
  

What can we offer?
twoday is located in modern offices in 30 locations in Norway, Sweden, Denmark, Finland, and Lithuania. We have a strong and unique social environment with highly engaged employees. If you are the candidate we are looking for, you will have a central role with exciting opportunities to develop in an international and innovative group, with exciting products and services within technology and software. You will also have the flexibility to "jump" and work from one of our headquarters in Oslo, Stockholm, Copenhagen, Helsinki, or Vilnius at times.

Diversity & Inclusion
Are you not meeting all the requirements listed? Studies have shown that women and other minority groups are less likely to apply for a job if they don't meet every qualification. We're dedicated to build a workplace of diversity and inclusion. If you are excited about this role but your previous experience does not match the job description, we encourage you to apply anyway.