Billie Tech Stack

B2B Buy Now, Pay Later platform powered by ML-driven credit and fraud decisioning

Financial Services Berlin, BE 51–200 employees Founded 2016 Privately Held

Billie operates a B2B BNPL payment platform built on Python, scikit-learn, XGBoost, and PyTorch—a data-science-heavy stack matched by hiring focused almost entirely on senior data roles. The project portfolio reveals a company in active transition from rule-based payment decisioning toward ML-driven credit and fraud prevention: they're building real-time decision engines, portfolio optimization models, and credit risk models while wrestling with integration complexity and recovery rate improvements. This is a fintech scaling its core underwriting logic.

Tech Stack 15 technologies

Core StackPython pandas scikit-learn PyTorch TensorFlow Snowflake BigQuery Tableau Docker Kubernetes Neo4j MySQL PostgreSQL XGBoost SQL

What Billie Is Building

◆Challenges

Optimizing real-time decision engine logic
Fraud prevention
Integrating new data sources
Credit risk
Portfolio optimization
Modeling complex business patterns
Improving decision engine logic
Improving recovery rates
Streamlining collections processes
Automation opportunities

▲Active Projects

Fraud prevention ml solutions
Portfolio optimization model
Deployment of ml services
Real-time decision engine optimization
Credit decision engine
Portfolio management system
Fraud prevention ml model deployment
Credit risk model production
Advanced multi-channel collection strategy
Process automation rollout

Hiring Activity

Accelerating9 roles · 5 in 30d

Department

Data

Finance

Seniority

Senior

Manager

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About Billie

Billie provides Buy Now, Pay Later payment solutions for B2B companies, allowing businesses to defer payment while suppliers get paid upfront. Founded in Berlin in 2016 by former Zencap founders, the company now employs over 180 people across 45+ countries. The platform relies on proprietary machine-learning risk models, fully digitized workflows, and a scalable tech foundation to underwrite and manage credit decisions. Revenue comes from both sides of the transaction: merchants adopting the checkout solution and the credit products themselves, underpinned by automated collections and portfolio management.

HeadquartersBerlin, BE

Company Size51–200 employees

Founded2016

Hiring MarketsGermany

Frequently Asked Questions

What tech stack does Billie use?

Python, pandas, scikit-learn, XGBoost, PyTorch, TensorFlow, SQL, Snowflake, BigQuery, Tableau, Docker, Kubernetes, Neo4j, MySQL, and PostgreSQL. Heavy emphasis on ML libraries and data warehousing.

What is Billie working on?

Fraud prevention ML models, credit decision engines, real-time decisioning optimization, portfolio optimization models, and collections process automation. Core focus is scaling ML-driven underwriting and improving recovery workflows.