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 across Europe and the US attract global merchants in segments such as e-commerce, travel, financial services and gaming. In June 2018, private equity firm Nordic Capital acquired a majority stake in Trustly with ambitions to support us in becoming the leading global online banking payments provider.
We are a diverse and fast-growing team of 350+ people with our headquarters in Stockholm, Sweden, and offices in Barcelona, Spain; Cologne, Germany; Helsinki, Finland; Lisbon, Portugal; London, UK; Örebro, Sweden; Redwood City, US; Sliema, Malta; and Vitória, Brazil. 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 Intelligence and Data Analytics team serves the whole organization with data insights. It consists of Data Scientists, Data Engineers and BI Developers. The team has been growing continuously with the rest of the company as the demand for data in the decision making process increases.
We have spent the last year building a scalable data platform on top of Google Cloud Platform to serve both our BI tool well as our statistical and machine learning models. We are now in a position where we are not limited by data but by people who turn data into actions, and that is where you come into the picture.
What you’ll do:
- Build predictive models to improve our understanding of what drives the usage of our products and the loyalty of our user base
- Analyze and dig into vast amounts of data to find actionable insights
- Develop and ship end to end machine learning solutions for automatic predictions and product decisions
- Work with stakeholders across the company to help them define their requirements: which are the best topics to investigate further given the data we have and what a predictive model could help answer?
- Define the scope of your investigations and find the areas where your work will have the biggest impact
- Communicate data-driven insights and recommendations to key stakeholders, who have a varying degree of technical knowledge
- Identify and implement new tools needed for your analysis; we prefer to work with open-source alternatives where possible
- A university degree in a Scientific, Engineering or Mathematical field
- Familiar with different techniques and approaches to regression, classification, clustering, a/b - testing, causal inference etc.
- Strong mathematical background with good foundations in both Bayseian and frequentist statistics and its applications
- Experience with Python/R and SQL
- Pragmatic and focused on achieving results for the benefit of the company, not only on a specific technique to get there, you take pride in finding simple solutions to easy problems
- Capable of interpreting loosely defined problems and pick up the necessary tools and knowledge needed to solve the problem at hand
- A communicative person who values building positive relationships with colleagues and stakeholders