Senior Data Science Consultant with Python, KRAKÓW
Must have
- Hands-on experience with Python for data analysis and data processing.
- Strong knowledge of data manipulation and analysis using Pandas and NumPy.
- Good understanding of SQL and working with relational databases.
- Basic knowledge of Machine Learning concepts and workflows.
- Experience with data wrangling, cleansing, and feature engineering.
- Strong analytical thinking and problem-solving skills.
- Experience working with structured and unstructured datasets.
- Ability to translate data into actionable insights and business value.
- Basic understanding of LLMs and Generative AI solutions.
Nice to have
- Experience with Big Data technologies such as PySpark or similar frameworks.
- Familiarity with cloud platforms such as GCP, AWS, or Azure.
- Experience with prompt engineering, RAG, or AI-powered applications.
- Exposure to MLOps practices and model deployment.
- Knowledge of data pipelines and data engineering concepts.
- Experience with data visualization tools such as Matplotlib, Seaborn, or Plotly.
- Experience working in regulated environments such as finance or banking.
Don't worry if you don't tick every box
We're looking for curious and analytical professionals who enjoy working with data and solving complex problems. If you meet most of the requirements and are excited about the opportunity, we encourage you to apply. We value learning agility, critical thinking, and a growth mindset as much as experience with specific technologies.
As a Data Analyst, you will design and develop data-driven solutions that help transform complex datasets into meaningful insights and business value. Working with Python, SQL, and modern analytics tools, you will analyze data, build machine learning models, and support data-informed decision-making across the organization.
You will collaborate closely with business and technical stakeholders to deliver reliable, high-quality analytical solutions while continuously improving data processes, methodologies, and best practices.
,[Design and develop data processing and analytical solutions in Python, Work with datasets to clean, transform and analyse data, Build and optimize machine learning models, Translate business requirements into data-driven solutions, Collaborate with stakeholders and engineering teams, Ensure quality, performance and reliability of data solutions, Contribute to continuous improvement of data practices] Requirements: Python, pandas, SQL, Relational database, Machine Learning, NumPy, AI, LLM, ML, Big Data, PySpark, Cloud platform, AWS, MLOps, Data pipelines, Data visualization, Matplotlib, GCP, Azure, Seaborn, Plotly