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9 часов назад

Lead Data Scientist (AI)

Формат работы
hybrid
Тип работы
fulltime
Грейд
senior/lead
Английский
b2
Страна
Germany
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
Lead Data Scientist (AI) (Credit Risk/ML): Designing, developing, and productionizing scalable machine learning solutions for credit risk and portfolio management with an accent on PD modeling, applied AI, and real-time decision engines. Focus on building production-ready LLM and generative AI solutions, optimizing complex risk models, and leading MLOps-enabled deployment across Engineering, Product, and Data Science.

Location: Berlin, Germany; hybrid work with up to 3 days per week from home

Company

hirify.global provides Buy Now, Pay Later payment methods and digital checkout solutions for B2B companies, supported by proprietary machine-learning risk models and a scalable technology platform.

What you will do

  • Own the credit risk modeling domain and a key business KPI with direct impact on P&L.
  • Design, develop, and productionize scalable machine learning solutions for credit and portfolio management.
  • Advance credit scoring with applied AI methods, including LLMs, RAG, AI agents, and foundation models.
  • Build PD, LGD, and EAD models, identify risk factors, and optimize real-time decision engine logic.
  • Design experiments and A/B tests for complex cross-domain problems and translate results into actionable insights.
  • Partner with Engineering, Product, and Data Science teams, contribute to system design, and mentor junior Data Scientists.

Requirements

  • 6+ years of Data Science experience with significant credit-domain expertise and deep experience in PD modeling, validation, and production monitoring.
  • Strong Python and SQL skills, including pandas, scikit-learn, XGBoost, PyTorch or TensorFlow, and data visualization with Tableau.
  • Hands-on experience evaluating, integrating, and fine-tuning LLMs and generative AI models in production.
  • Experience deploying and productionizing ML services using MLOps practices such as Docker, Kubernetes, event-driven architectures, and model monitoring.
  • Strong quantitative analysis, data mining, business acumen, communication, and data storytelling skills.
  • Experience with LGD, EAD, limit policies, portfolio management, or graph databases such as Neo4j is highly valued.

Nice to have

  • Broader credit risk experience across LGD, EAD, limit policies, and portfolio management.
  • Hands-on experience with Neo4j or other graph databases for interconnected data.

Culture & Benefits

  • Flexible working hours and a hybrid work model.
  • 30 days of vacation, sabbatical opportunities, and additional child sickness leave for parents.
  • Virtual Shares Incentive Program and an annual professional development budget.
  • Discounted Berlin public transport, Deutschland-Ticket, or JobRad.
  • Free German group classes and an English-speaking, multicultural team.
  • Company events, interest groups, a run club, and game nights.

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