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About the Role

Join our strong international team to transform the traditional debt collection industry with innovation and a drive for excellence. Work on improving and maintaining our data architecture using machine learning and artificial intelligence.

Responsibilities

• Be part of our Data Science team to further optimize our innovative product based on machine learning and artificial intelligence.
• Work on advanced and demanding AI fields such as large language models.
• Identify, understand, structure and solve complex problems in a driven and pragmatic manner.
• Work on projects that deliver measurable value to our business.
• Experiment with new technologies and acquire new skills to find clever solutions to the unique challenges we will encounter along the way.
• Communicate between all stakeholders (data scientists, lead developers, product management, business owners) and present technical product concepts.

Requirements

• Degree in Data Science, Computer Science, Mathematics or similar.
• 6+ years experience as Data Scientist, ideally in a startup or fintech company.
• Extensive and hands-on experience with deployment of (ideally open source) LLMs (hosting, fine-tuning, prompt engineering, evaluation).
• Experience automating complex processes using LLMs, reducing system latency, increasing efficiency, etc.
• Deep knowledge of server management, GPU orchestration, and computational optimization techniques.
• Extensive experience with Python and with data processing packages (e.g. Pandas, Numpy) and machine learning frameworks (e.g. pytorch, scikit-learn, transformers).
• Familiarity with web frameworks like Flask or FastAPI.
• Deep knowledge of relational databases such as MySQL or PostgreSQL.
• Experience with agile development practices such as TDD/BDD, continuous integration, refactoring, code reviews, etc.
• Experience with cloud-based infrastructure solutions, such as AWS.
• Experience with reinforcement learning is a strong plus.
• Excellent English speaking and writing skills.

Skills

• Machine Learning
• Artificial Intelligence
• Large Language Models (LLMs)
• Python
• Pandas
• Numpy
• Pytorch
• Scikit-learn
• Transformers
• Flask
• FastAPI
• MySQL
• PostgreSQL
• AWS
• Reinforcement Learning

Location

• Berlin

Work Type

• Hybrid

Experience Level

• 6+ years experience as Data Scientist

Education Level

• Degree in Data Science, Computer Science, Mathematics or similar

Benefits

• Visa sponsorship
• Thriving, financially stable company
• Strong experienced international team to support and mentor you along the way
• Smooth onboarding process
• International team of 30+ nationalities with professionals and experts
• Flat hierarchy
• Transparent and appreciative feedback culture
• Monthly all hands meetings
• Annual feedback and evaluation cycle
• Regular 1-on-1s with your lead
• Well-structured onboarding process
• Supportive and welcoming colleagues
• Personal learning & development budget
• German and English language courses
• Unlimited employment contract
• Flexible working hours
• 28 vacation days
• Company pension plan
• Partly covered Deutschlandticket (public transport)
• Access to “Corporate Benefits” voucher platform
• Fun company summer and Christmas parties
• Regular team events

About the Company

• We are rethinking debt collection with our digital debt collection solution, characterized by our high customer orientation and efficiency standards. By using artificial intelligence, we are combining technology with behavioral science and so we are able to contact customers individually and in a simple way throughout the entire collection process.
• Strengthened by one of the most renowned private equity firms in the fintech sector, Pollen Street, as well as partnerships with other investors such as Zalando Payments, PAIR Finance offers an excellent opportunity to dive deep into and actively shape the fintech industry.

Equal Opportunity

• PAIR Finance is an equal-opportunity employer. We value a diverse team and an inclusive culture. We welcome applications from all qualified individuals regardless of ethnicity, color, religion, gender, sexual orientation, gender identity or expression, age, national origin, marital status, or disability.