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HybridKraków, Lesser Poland, Poland
Job Summary
Develop machine learning, modelling, and optimization solutions that drive measurable business value and operational performance. Apply predictive and prescriptive analytics to support scenario evaluation, decision-making, and performance improvement across the value chain. Translate business problems into analytical frameworks, partnering with stakeholders and technology teams to validate solutions and ensure successful deployment into digital products. Communicate insights and recommendations clearly to influence data-driven decisions. This role requires a Bachelor's degree in a quantitative discipline and 5+ years of experience in data science, with a hybrid schedule of four days in the office in Kraków.
Required Qualifications
- Bachelor's degree in Data Science, Computer Science, Engineering, Applied Mathematics, Operations Research, Statistics, Physics, or a related quantitative discipline
- 5+ years of experience in data science, advanced analytics, machine learning, modelling & optimization, or related disciplines
- Strong experience applying machine learning, statistical methods, modelling and optimization techniques to solve real business or operational problems
- Proficiency in Python and the modern data science ecosystem, with experience working with SQL and diverse structured and unstructured datasets
- Experience developing, validating, and deploying analytical, predictive, or prescriptive solutions in production environments
- Strong problem-solving, communication, and stakeholder engagement skills, with the ability to explain complex concepts and influence decision-making across technical and non-technical audiences
- This position is based in Kraków and operates in a hybrid working model, requiring employees to work from the office 4 days per week
Desired Qualifications
- A Master's degree or PhD is advantageous
- Experience within Oil & Gas, Energy, Manufacturing, Logistics, Supply Chain, or other industrial sectors
- Experience with mathematical optimization and metaheuristic techniques
- Experience developing decision-support tools, digital twins, simulation models, or scenario-planning solutions
- Familiarity with modern software engineering practices, version control systems (e.g., GitHub), Agile methodologies, and code quality standards
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