Role overview
Junior Data Scientist
The person in this role will work with project teams developing modern data platforms in cloud environments for global brands. They will work in an international environment, grow their expertise in Data & AI solutions, learn the latest technologies in this area and support the principles of the DataOps manifesto.
Warsaw
Hybrid/Onsite
Responsibilities
Working closely with clients across industries - from analyzing problems and identifying areas for improvement to supporting the design and presentation of advanced analytics and machine learning solutions
Building, evaluating and deploying machine learning models - from classical statistical approaches to LLM-powered applications
Designing and implementing GenAI solutions including RAG pipelines, agentic workflows and LLM-based automation
Contributing to MLOps practices - model versioning, experiment tracking, CI/CD for ML, monitoring and observability in production
Participating in the full project lifecycle: from business and data analysis, through prototyping and development to production deployment and result validation
Requirements
Minimum 1 year of experience in Data Science / ML Engineering (internships, commercial projects, or strong open-source/research contributions)
Strong programming skills in Python
Solid understanding of fundamental statistical and ML models
Hands-on experience with at least some of LLMs, prompting techniques, RAG architectures, fine-tuning, evaluation & guardrails, agentic frameworks (e.g. LangGraph)
Knowledge of ML libraries (e.g., PyTorch, Tensorflow)
Ability to analyze problems and synthesize solutions
Basic knowledge of selected ML solution lifecycle management platforms (e.g. MLflow, Azure ML, Amazon SageMaker)
Knowledge of SQL, comfortable querying and transforming data in relational databases
Ability to write clear, structured code following good programming practices
Familiarity with git repositories and tools such as JIRA, Confluence, Teams
Very good knowledge of English (B2+) enabling work in an international environment
We offer
Global projects in clouds - we work with clients from all over the world based on modern cloud technologies
Certification reimbursement - develop your skills and obtain certifications such as Microsoft, Amazon Web Services, Databricks, and ISTQB. We cover the cost of exams
Time to learn - take advantage of 60 paid hours per year for learning and use the Buddy Program, which supports you during your first months on the job
Flexible approach - connect studies with your career. Adjust your schedule to your needs thanks to flexible working hours
Personalized benefits - medical care, subsidized sports packages, language tuition, new employee referral bonus (up to PLN 15,000) as well as annual and media bonus
What you'll work on
Working closely with clients across industries - from analyzing problems and identifying areas for improvement to supporting the design and presentation of advanced analytics and machine learning solutions
Building, evaluating and deploying machine learning models - from classical statistical approaches to LLM-powered applications
Designing and implementing GenAI solutions including RAG pipelines, agentic workflows and LLM-based automation
Contributing to MLOps practices - model versioning, experiment tracking, CI/CD for ML, monitoring and observability in production
Participating in the full project lifecycle: from business and data analysis, through prototyping and development to production deployment and result validation
What we're looking for
Strong programming skills in Python
Solid understanding of fundamental statistical and ML models
Hands-on experience with at least some of LLMs, prompting techniques, RAG architectures, fine-tuning, evaluation & guardrails, agentic frameworks (e.g. LangGraph)
Knowledge of ML libraries (e.g., PyTorch, Tensorflow)
Ability to analyze problems and synthesize solutions
Basic knowledge of selected ML solution lifecycle management platforms (e.g. MLflow, Azure ML, Amazon SageMaker)
Knowledge of SQL, comfortable querying and transforming data in relational databases
Ability to write clear, structured code following good programming practices
Familiarity with git repositories and tools such as JIRA, Confluence, Teams
Very good knowledge of English (B2+) enabling work in an international environment