Senior Analyst - Fraud

What you'll do:

• Use statistical analysis tools and techniques to develop automated fraud detection and real-time decisioning strategies for Klarna's card products.
• Collaborate with Data Scientists to build and implement fraud pattern models.
• Work with other teams and competences across the business (particularly Engineering, Product and Commercial) to devise robust fraud strategies for new products and markets.
• Create, test and monitor new fraud tools and strategies from scratch.
• Work on proof of concepts involving new technologies and proactively seek out vendor and internal solutions to fraud problems.
• Ensure metrics and strategies are fit for purpose in terms of the current fraud environment and emerging threats.
• Work closely with the investigations team to understand threats and develop mitigations.
• Communicate and involve stakeholders to respond to any fraud related incidents as the first touchpoint for Legal, Sales, Engineering, Data Science and other partners.
• Act as a trainer and consultant for our internal and external stakeholders.

Who you are:

• Klarna is looking for ambitious people with significant drive who enjoy a fast paced international working environment. You will play an important role in taking Klarna to the next level! 
• At Klarna we embrace change, we appreciate when you challenge the status quo and are persistent.

You should have:

• 3 to 7 years of relevant experience in analytics.
• Solid analytical thinking abilities, decision making and problem solving skills.
• Proficiency in SQL with the ability to analyze large quantities of data with statistical analysis tools.
• Experience in the entire Analytics lifecycle, from requirements gathering, data extraction, manipulation and analysis to sharing insights and advising on decision making as well as implementing changes.
• Excellent track record in optimizing business performance and identifying gaps in business strategy, with a focus on financial services, ideally fraud.
• Understanding of the underlying business and the need of calibration to reach the agreed balance between risk and revenue
• Working proficiency and communication skills in verbal and written English.
• Demonstrated stakeholder management skills.
• Passion for learning and teaching others about fraud.
• A university degree in a numerate subject (e.g. Economics, Science, Engineering, Mathematics)

You might also have:

• Experience​ ​of​ ​decision​ ​systems,​ ​including​ ​rule/strategy​ ​implementation​ ​and testing​ ​is​ ​preferred.
• Experience from working with Fraud, ideally within finance/payments and the retail industry.
• Knowledge of external fraud data sources and use cases to prevent fraud.
• An understanding for how to perform data extraction and manipulation in multiple programming languages is a plus (Python, R, MatLab, Java, C# etc…).