Data Scientist (Generative AI)

Summary

Join ELEKS Artificial Intelligence Office and become our Data Scientist (Generative AI) in Poland, Croatia, or Ukraine! This role involves leading complex data science projects for a British company producing zero-carbon electricity. You will design and implement analytical solutions using advanced methods, including AI and large language models. Effective communication of data-driven insights to both technical and non-technical stakeholders is crucial. The position requires expertise in generative AI, NLP, and machine learning, along with strong analytical and modeling skills. You will also contribute to evolving data and AI policies and ensure compliance with organizational standards.

Requirements

• Educated to degree or equivalent discipline with a solid analytical background as well as commercial experience with data science and machine learning techniques
• Experience in building Generative AI applications (AgenticAI, RAG, etc.)
• Strong working knowledge of data science languages (SQL, Python, R, or equivalent) and cloud services
• Skilled in advanced modelling techniques, including the ability to peer-review other data scientists' work
• Strong understanding of generative AI, NLP, and machine learning concepts
• Able to contribute to evolving data and AI policies, standards, and guidelines for methods and tools
• Ability to develop accurate models from first principles, ensuring business value is central to all data-driven outcomes
• Competence in data modelling and managing data requirements
• Ability to rapidly absorb and critically assess new information
• Effective communication skills for engaging with diverse stakeholders
• Upper-Intermediate level of English

Responsibilities

• Lead the delivery of complex data science projects from planning through execution, ensuring alignment with time, cost, and quality objectives
• Design and implement analytical solutions by applying advanced data science methods, including artificial intelligence and large language models, while staying current with technological developments
• Effectively communicate complex, data-driven insights to non-technical and technical stakeholders, articulating business impact and value
• Conduct time-boxed data exploration to rapidly test hypotheses and determine viability before committing significant resources
• Drive adoption of analytical outputs across the business by ensuring clarity, relevance, and engagement with key stakeholders
• Proactively identify and mitigate risks using RAID frameworks, ensuring project continuity and result integrity
• Track and assess benefits derived from data science initiatives, with a focus on high-value outcomes and continuous improvement
• Ensure compliance with organisational standards, governance frameworks, and ethical data practices

Benefits

• Close cooperation with a customer
• Challenging tasks
• Competence development
• Team of professionals
• Dynamic environment with low level of bureaucracy