Principal Data Scientist, Marousi, Hybrid (2-3)

Our client is a global software company operating in the renewable energy sector, delivering software platforms for utility-scale solar, wind, and battery storage operators across international markets. The role exists due to the continued growth of battery storage within the company’s customer fleet and the expansion of its advanced analytics capabilities.

The Role

You’ll contribute to the analytical work programme focused on battery energy storage systems, developing production-grade machine-learning and statistical models that support asset health, degradation analysis, anomaly detection, and operational optimisation. Working closely with MLOps and platform engineering teams, you’ll help translate advanced analytical research into scalable production capabilities.

Within your first six months, you’ll be expected to contribute validated analytical models for battery performance and degradation monitoring, collaborate on production deployment workflows, and support the evolution of the platform’s storage analytics roadmap.

What You’ll Bring

• PhD, or equivalent industry-recognised expertise, in a quantitative field such as electrochemistry, electrical engineering, applied mathematics, statistics, or physics
• 5+ years of professional experience applying machine-learning and statistical methods to industrial time-series datasets
• Strong Python skills including NumPy, Pandas, and scikit-learn, together with experience using deep-learning frameworks such as PyTorch or JAX
• Demonstrable understanding of battery physics and degradation mechanisms including calendar fade, cycle fade, lithium plating, SEI growth, and thermal management
• Experience building analytical models for areas such as state-of-health estimation, anomaly detection, efficiency monitoring, or dispatch-quality analysis
• Fluency with AI-assisted engineering and agentic coding workflows
• Strong written and verbal communication skills in English

Nice to Have

• Experience working with fleet-scale battery energy storage datasets
• Familiarity with augmentation planning, warranty modelling, and capacity-test interpretation
• Open-source contributions or peer-reviewed publications related to storage, grid systems, or applied analytics

What’s in it for You

The role offers a salary commensurate with experience (€5000 - €6500) and the opportunity to work on advanced analytics for large-scale battery energy storage systems. It follows a hybrid working arrangement, with two days onsite and three days remote each week in Athens, and provides a collaborative international environment that brings together applied science, machine learning engineering, and renewable energy technology. Additional benefits include a monthly meal allowance, private health insurance, and an annual performance bonus.