Data Scientist

Capco Poland is a global technology and management consultancy partnering with leading organizations in banking, payments, capital markets, wealth, and asset management. The company focuses on technology, data, and AI to solve complex challenges and deliver real-world solutions in financial services.

• Practical experience developing and evaluating machine learning, statistical, or AI models.
• Strong Python skills and experience with modern data science and ML ecosystem.
• Understanding of model development, experimentation, feature engineering, validation, and performance evaluation.
• Experience deploying ML solutions beyond experimentation into real-world applications.
• Strong software engineering skills including clean code, testing, design patterns, and architectural principles.
• Experience building AI-powered applications, services, or platforms.
• Knowledge of API design, microservices, distributed systems, or cloud-native development.
• Hands-on exposure to Generative AI, LLMs, Retrieval-Augmented Generation (RAG), agents, or related AI architectures.
• Experience building or operating ML/AI infrastructure and production pipelines.
• Practical knowledge of Docker and Kubernetes.
• Experience with CI/CD, automation, model deployment, monitoring, observability, and model lifecycle management.
• Understanding of scalable, reliable, and secure production environments for ML and AI workloads.
• Around 4+ years of professional experience in software engineering, data science, machine learning, MLOps, AI engineering, or related area.
• University degree in Computer Science, Mathematics, Physics, Engineering, or related discipline, or equivalent practical experience.
• Strong problem-solving skills, engineering mindset, and understanding of software engineering and application design best practices.
• Ability to work effectively in an Agile, collaborative environment.
• Curiosity and desire to continuously learn as AI technologies evolve.
• Ability to communicate technical ideas clearly and collaborate with technical and non-technical stakeholders.

Nice to have:

• Experience with frameworks and platforms such as LangChain, Haystack, Kubeflow.
• Designing LLM/RAG architectures, vector search, embeddings, AI agents, or GenAI applications.
• Experience with major cloud platforms and cloud-native AI/ML services.
• Experience designing and developing microservices architectures.
• Familiarity with established MLOps frameworks and ML lifecycle best practices.
• Experience deploying and operating workloads on Kubernetes.
• Knowledge of DevOps, Infrastructure as Code, CI/CD, observability, and production monitoring.
• Experience working with enterprise-scale data and AI environments.

• Design, develop, and productionize innovative AI and machine learning solutions addressing real business challenges.
• Explore and implement approaches across Machine Learning, Generative AI, Large Language Models (LLMs), and intelligent automation.
• Build AI applications and services using Python, APIs, microservices, and cloud-native technologies.
• Develop reusable AI/ML libraries, frameworks, components, and common assets.
• Design and maintain ML and AI pipelines for full lifecycle support.
• Build scalable, resilient, secure, and maintainable systems for production-grade AI workloads.
• Apply modern MLOps, DevOps, and software engineering practices.
• Work with Docker, Kubernetes, cloud platforms, CI/CD pipelines, model registries, monitoring, and automation tooling.
• Collaborate with engineers, data scientists, architects, business stakeholders, and client teams.
• Define and promote engineering standards, architectural principles, reusable patterns, and best practices for AI development.
• Stay updated on emerging AI technologies and evaluate their value for clients.

Informujemy, że administratorem danych jest Capco_ z siedzibą w Warszawie___, ul. Rondo ONZ 1_____(dalej jako "administrator"). Masz prawo do żądania dostępu do swoich danych osobowych, ich sprostowania, usunięcia lub ograniczenia przetwarzania, prawo do wniesienia sprzeciwu wobec przetwarzania, a także prawo do przeniesienia danych oraz wniesienia skargi do organu nadzorczego. Dane osobowe przetwarzane będą w celu realizacji procesu rekrutacji. Podanie danych w zakresie wynikającym z ustawy z dnia 26 czerwca 1974 r. Kodeks pracy jest obowiązkowe. W pozostałym zakresie podanie danych jest dobrowolne. Odmowa podania danych obowiązkowych może skutkować brakiem możliwości przeprowadzenia procesu rekrutacji. Administrator przetwarza dane obowiązkowe na podstawie ciążącego na nim obowiązku prawnego, zaś w zakresie danych dodatkowych podstawą przetwarzania jest zgoda. Dane osobowe będą przetwarzane do czasu zakończenia postępowania rekrutacyjnego i przez okres możliwości dochodzenia ewentualnych roszczeń, a w przypadku wyrażenia zgody na udział w przyszłych postępowaniach rekrutacyjnych - do czasu wycofania tej zgody. Odbiorcą danych jest serwis Rocket Jobs oraz inne podmioty, którym powierzyliśmy przetwarzanie danych w związku z rekrutacją.