Data Scientist
vor 7 Monaten
We dare to design the future of payments. Ratepay is energy and diversity and: custom-made state-of-the-art payment solutions. Established in 2009 we were a fintech before the word fintech even existed. Today we are the number one white-label Buy Now Pay Later payments provider in Europe handling over 2.5M transactions per month and we’re constantly growing.
We are where we are because we work together as one team. Because we got the freedom to execute ideas. And above everything: because we never stop improving. Here it is all about shared goals not about the big ego. We are dedicated pros (more than 250 of them) not cons. We embrace being courageous, committed and decisive, warm-hearted and having a will to win.
We have our origin in the heart of the payment scene and cover the whole value chain from integration support to the dunning process with a core of AI-based risk management. With us, you can integrate direct debit, instalments and prepayment. In other words: the favourite payment methods in Germany, Austria and Switzerland (the Dutch like it too). Located in the middle of Europe’s fintech metropolis (Berlin) we are proud to work with major partners such as Eurowings, Ebay and About You and hundreds more.
Tasks
As a Senior Full Stack Data Scientist (M/F/d) you will improve the effectiveness of Ratepay's real-time fraud prevention engine by enhancing its logic and refining both its research and production pipelines (on AWS). You will leverage advanced Machine Learning algorithms to ensure no fraudster makes it past our systemsYou will have end-to-end ownership of Data Science projects, from ideation to production, and will contribute to mentoring junior team members while managing subcomponents of the fraud ML infrastructure.
THE ROLE
**1. Enhance Fraud Prevention Systems**: Utilize advanced feature engineering and all the other techniques from your data science toolkit to continuously improve our fraud prevention systems.
**2. ML Workflow Improvement**: Collaborate with cross-functional teams to optimize our ML workflows, from data collection and preprocessing to model training and deployment.
**3. ETL Pipeline Development**: Create robust ETL pipelines to ensure our algorithms have access to the data they require. Implement ETL processes to support real-time fraud prevention.
**4. End-to-End Project Ownership**: Take full ownership of Data Science projects, from the initial ideation stage through proof of concept and deployment into production, ensuring that projects align with business goals and deliver tangible results.
**5. Mentorship and Knowledge Sharing**: Share your expertise and best practices with junior team members. Provide guidance on data science methodologies, coding standards, fostering a culture of continuous learning within the team.
**6. Documentation and Reporting**: Maintain comprehensive documentation of projects, workflows, and pipelines.
**Core skills**:
- Programming Skills: Demonstrated expertise in Python, including strong engineering skills. Proficient in writing unit tests and familiar with best practices for writing clean code, including tools like pre-commit and black.
- Data Engineering: A general understanding of SQL and SQL databases, with the ability to retrieve and manipulate data efficiently. Proficiency in building data pipelines for research purposes, enabling the feeding of data to machine learning models. Ideally, the capability to create simple data pipelines for production use.
**Requirements**:
\*\*This is a FULL STACK Data Scientist role, which means we require wide-ranging experience, not someone traditionally focused solely on research\*\*
- You have completed a degree in Data Science, Computer Science, Information Technology, Statistics, or a related field and 5+ years of professional experience as a Full Stack Data Scientist.
- Strong engineering skills in Python, with a deep understanding of clean code principles (e.g., pre-commit, black, code reviews).
- Good understanding of SQL and SQL databases, with the ability to efficiently retrieve and manipulate data. Capability to design and build data pipelines that feed models in research environments, and, ideally, experience in constructing simple, production-ready pipelines.
- Proficiency in deploying machine learning systems in a scalable, reliable, and low-response-time production environment.
- Proficiency in the design of algorithmically powered products, including the ability to conceptualize and develop innovative solutions to complex problems.
- "Getting Things Done" Attitude: A proactive and results-oriented mindset, demonstrating a strong commitment to delivering tangible outcomes and driving projects to completion.
**Benefits**:
**Stability & Innovation**: Become part of a dynamic fintech company that is transforming the financial industry through innovation and technology.Ratepay is part of the NEXI Group - one of the biggest financial groups in Europe
**Team & Culture*
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