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Fraud Data Analyst (w/m/d)

Billie

Billie

IT, Accounting & Finance, Data Science
Berlin, Germany
Posted on Thursday, November 9, 2023

We are Billie, the leading provider of Buy Now, Pay Later (BNPL) payment methods for businesses, offering B2B companies innovative digital payment services and modern checkout solutions. We are to create a new standard for business payments and have made it our mission to simplify the purchasing experience for all businesses making it a tool for growth. Our solutions are based on proprietary, machine-learning-supported risk models, fully digitized processes and a highly scalable tech platform. This makes us a deep-tech company building financial products, not the other way around. We love building simple and elegant solutions and we strive for automation and scalability.

About the role:

We are looking for a diligent Anti-Fraud Analyst to join our team and contribute to the development and enhancement of our anti-fraud systems.

  • Develop and refine anti-fraud rule logic, including the integration of machine learning algorithms.
  • Design and maintain dynamic dashboards to monitor and display the effectiveness of anti-fraud measures.
  • Execute data engineering tasks, including the creation and regular updating of anti-fraud tables.
  • Conduct daily reviews of fraud cases to pinpoint vulnerabilities within the anti-fraud system.
  • Proactively search for and gather pertinent internal data to aid developers, including defining terms and compiling tables with specific information.
  • Create, review, and update anti-fraud rules, ensuring they are current and effective.
  • Document existing fraud detection methodologies and metrics.
  • Innovate by developing machine learning-based methods for fraud detection, including graph clustering algorithms to identify fraud communities.

Who we are looking for:

  • You have at least 2+ years proven experience in anti-fraud analytics or data engineering
  • You have excellent proficiency in SQL
  • You are proficient in data visualization and analytics tools, especially Tableau and Power BI
  • You have keen investigative skills to identify and analyze fraud patterns
  • You had the chance to work in a fast-paced and dynamic environment

What we offer:

  • Flexible work hours and trust in your ability to deliver, empowering you to take control of your work-life balance
  • Hybrid working approach enabling a good balance working from home and the office
  • One of the best Virtual Shares Incentive Programs in the market, so that everyone at Billie is invested in our success
  • Our “Catch a Ride with Billie” program, that enables discounted access to Berlin Public Transport (BVG)
  • A yearly development budget to broaden your skill set and horizons
  • Free German group classes
  • An English-speaking, multicultural team with more than 46 nationalities
  • Great office space at Checkpoint Charlie with free gym access, barista coffee, drinks and more

Billie offers you the opportunity to be a part of one of the fastest-growing Fintech startups in Europe following the mission to innovate to create new freedom for businesses of all sizes. Our combined decades of experience in B2B Financing and Payments in a market thirsty for innovation and change make this a fantastic possibility to get into the most dynamic space in tech.

Join an international team of talented, passionate people where drive and merit matter. We work in nimble, cross-functional teams with open communication lines across the company. You’ll be surrounded by smart people from a wide variety of backgrounds from which you can learn and that want to learn from you.

Are you ready to join Billie?

Billie is proud to be an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment in our workplace. By embracing talents and abilities of all kinds, we aim to boost motivation and team creativity. We do not discriminate on the basis of race, religion, national origin, age, marital status, gender, political views, beliefs, sexual orientation, color, disability status, or any other demographic factors.