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Full-time Copenhagen

Senior Data Scientist

Who we are

We’re a team driven by the belief that we can radically change the world of work. We believe – and hear from our customers every day – that when an organisation understands itself better it can create more fulfilling jobs, and grow in ways never before imagined.

Enterprises big and small trust our products to provide visibility and clarity in areas once characterised by hearsay and uncertainty. With the insights delivered by Peakon, these organisations become more agile, responsive, and able to make the changes and investments that their employees care about most. 

We’re in the business of creating great places to work, so it should be no surprise that this is our highest priority at Peakon. With ambitions as big as ours, we see individual growth and development as the key strategy for growing our business. 

Trust and transparency guide everything we do here. You’ll find an open salary model, unlimited vacation, minimal hierarchy, and maximum freedom to develop and execute your own ideas. Our style of collaboration is based on honesty and friendship, and we always love making new friends...


At Peakon, data is at the heart of everything we do. Our mission is to deliver the insights that help everyone in an organisation reach their full potential. The key to making this possible is generating persuasive, actionable recommendations from the data we collect, and communicating it in a clear and concise way. This enables managers and executives to make the improvements that really matter to their employees and see a big impact on their business as a result.

You will lead the data science team and drive us towards our mission. You will be responsible for identifying opportunities, testing and validating ideas, implementing solutions and getting the resulting insights into the hands of our users. 

In all aspects of the product you will be a key part of providing analytical insights to service our customers in understanding their engagement issues. You will lead the development of algorithms and statistical models that are adaptable and flexible enough to give any customer insights into their data.

You will work with product management to lay out our product roadmap and direct our efforts where they have the biggest impact. 

Who you are

You love data and the endless possibilities it offers to learn and gain new insights. You have a strong academic foundation, and keep on top of new developments in the field. You have extensive practical experience working as a data scientist and can quickly go from idea to implementation. You believe that data science should be analytical: whilst the underlying math and statistics may be complicated to explain, the reasons why we have recommended something should be easy to understand.

You are looking for an opportunity to grow with a startup and help define and shape the data science team in data-centric company.

Our ideal candidate

  • Strong academic track record within quantitative fields (ML, statistics, econometrics, financial engineering etc.). Preferably published articles.
  • Experience with R and Python.
  • 2-3 years experience with product development where statistical / machine learning parts play a core role.
  • Experience with API: Science-as-a-Service way of thinking.
  • A good presenter who is able to communicate data science to people of varying technical ability.
  • Experience facing customers and understanding the root cause of product inputs.

The tech

We make it a priority to stay at the cutting edge on tech. We are highly motivated by learning and growing in our roles, and constantly evolving is a key part of that. 

We are hosted in Heroku and AWS, our primary development language is Javascript, with Python and R used extensively for data science. We are big fans of automated testing, and have unit, integration and UI tests throughout the stack. We like to automate as much as we can, so we can focus our time where it matters.

The data science stack currently revolves around Python utilising NumPy, SciPy, SciKit Learn and Pandas along with some R packages. We utilize a broad spectrum of techniques from both the realm of statistics and machine learning. The tools we use range from significance testing, regularisation models for feature selection, imputing missing data patterns or building topic detection models using Support Vector Machines. We seldomly build statistical models with the goal of pure prediction - all models should have some sort of analytical aspect built in that we can then convey to customers. Along with the statistical models we also build software that can put together the words explaining the intuition behind our recommendations.

Senior Data Scientist
Full-time - Copenhagen

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