Data Scientist
Location
AI Core
Core Grid Application division
Key responsibilities
- A ctive participat ion in all stage s of the software development lifecycle (from requirement analysis to testing and verification)
- Collecting, preprocessing, and analyzing large datasets to ensure the quality and relevance of data used in AI models.
- Integration of ADMS with AI Models
- Improving the safety net of team's functionalities
- Help team to detect areas for improvement in software and processes
Qualifications/experience
- Strong understanding of machine learning algorithms and their practical applications (not just basic knowledge).
- Proven experience in developing and deploying AI/ML models in production environments.
- Hands-on experience with data engineering and data pipeline design, including data preprocessing and feature engineering.
- Experience with cloud platforms (Azure, AWS, or GCP) for AI/ML solutions.
- Track record of contributing to complex projects and mentoring junior team members.
Skills
- Ability to quickly adapt and integrate emerging technologies into existing workflows.
- Ability to work as a part of a team
- Advanced proficiency in C# and Python, including writing clean, maintainable, and optimized code
- Good organizational skills
- Responsibility and accuracy in performing tasks
- Thinking outside the box
- Great troubleshooting skills and analytical mindset
- Fluent in English
- Practical experience with ML Flow for experiment tracking and model management.
- Deep understanding of vector databases and modern AI architectures, including Small Language Models (SLMs) and Large Language Models (LLMs).
- Knowledge of MLOps best practices, including CI/CD for ML pipelines.
What we offer
- Pleasant working environment in a g reat team with experienced engineers willing to support and share their knowledge
- Opportunity for constant personal improvement in different areas
- Opportunity to learn and implement various AI models in ADMS software
- Opportunity to understand the real business use cases
- Collaboration with colleagues from different organizations
- Hybrid work model and flexible hours.
- Private health insurance.
- 24-30 days of annual leave.
- Financial, legal, and psychological assistance program.
- Summer recharge program (July & August).
- Gym & sports activities.
- Family-friendly policies (Parental & Care leave).
- Learning & development budget for certifications.
- Recognition and rewards through our StepUp platform.
- Career growth in a global sustainability leader company .
Bring your data science expertise to a team that's ready to support your growth - apply today!
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