Data Scientist / Stockholm

At Trustly, we’re passionate about simplifying the way people pay and get paid online. We are a licensed payment institution and our B2B products available in 29 European countries attract global merchants in segments such as e­-commerce, travel, financial services and gaming. In 2017, we processed 44% of our total payment volume since our founding in 2008, which is a testament to our fast growth, and today we process nearly 4 million monthly transactions.

We are a diverse and fast-growing team of 210+ people with our headquarters in Stockholm, Sweden, and regional offices in Spain, Malta, Germany and the UK. Together we are leading the development of the payments industry and the work you’ll do here will make a great impact.

About the Business Insights and Data Analytics team:


Trustly’s Business Insights and Data Analytics team serves the whole organization with data insights. It currently consists of one BI Developer and one Data Engineer but as our company grows, so do the demands on the team. We have recently rolled out Qlik Sense as our analytics tool within the organization, which has helped our stakeholders gain a lot of insights. While Qlik Sense solves most of our reporting and data discovery needs, there are still questions that require more sophisticated approaches. That is where the need for a Data Scientist comes in.

What you’ll do:

  • Build better predictive models to improve our understanding of what drives the usage of our products and the loyalty of our user base
  • Define the scope of your investigations and find areas where your work will have the biggest impact, together with the rest of the BI and Data Analytics team and other stakeholders within the company
  • Identify and implement new tools needed for your analysis; we prefer to work with open-source alternatives on Linux where possible
  • Present your findings to non-technical people (i.e. product management, commercial stakeholders, management etc.)
  • Work with stakeholders to define their requirements: help them choose the best topics to investigate further given the data we have available and what a predictive model could help answer

You are/have:

  • A university degree in a Scientific, Engineering or Mathematical field
  • A few years of experience building statistical models to answer complex questions
  • Good knowledge with Python/R and SQL
  • A self-starter - As you’ll be one of the first people in the organization working with these methodologies, you’ll have a big influence on what tools and methods we should use and you need to help the team drive their implementation
  • Someone who knows and understands how to apply and interpret complex models and techniques, but often chooses to use a simpler model when it gives equally good results given the question at hand and the data available

Thank you!

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