Data Scientist (w/m/d)

at  Billie

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.

WHO WE ARE LOOKING FOR:

• 3+ years of experience in a data science, machine learning, or engineering role
• You are proficient in Python (pandas, scikit-learn, xgboost), R (tidyverse/tidymodels packages) and SQL (MySQL, Postgres, Snowflake)
• You have experience with binary classification (boosted trees and similar models), explainable ML, graph networks analysis and anomaly detection
• You have eperience with version control systems (Git, others)
• You had insights with DVC and similar MLOps tools (nice-to-have)
• You have practical experience working across all stages of ML projects from conception to prod, either independently or under supervision of a senior
• You worked on detecting and analyzing fraud before
• You have experience managing and communicating to non-technical stakeholders

ABOUT THE ROLE:

As a Data Scientist, you will be part of the bigger decision science team, and will be contributing to one of our core decision areas, responsible for fraud mitigation, which has a direct impact on our business at Billie. In this role, you will build experiments to test your hypotheses, perform in-depth analysis and investigation to understand fraud patterns, then translate these findings into scalable predictive models. You will have the visibility to showcase your impact across stakeholder groups, which includes counterparts in product and engineering, but also directly to our leadership team.

IN THIS ROLE, YOU WILL:

• Apply your expertise in quantitative analysis, data mining, data science, and the presentation of analytics results to understand fraud, how it relates to Billie’s strategy and products, and how to prevent it
• Build advanced predictive models to understand the impact of specific fraudulent behaviors, trends, and patterns
• Work as a part of cross-functional teams of data and software engineers, analysts, product managers, operations, and business leaders to minimize impact of fraudulent behavior
• Communicate data-informed insights and recommendations to key stakeholders, discuss requirements with engineering and product partners for efficient implementation
• Have the opportunity to discovery new opportunities and own development from discovery to solutioning
• Have a measurable impact on future of Billie!