Data Scientist II

Join the Market Leader in Electric Power Data and Analytics Solutions   The electrical grid is the largest and most complicated machine ever built. Yes Energy’s industry-leading electric power trading analytics software provides real-time visibility into the massive amount of data generated by the North American electrical grid daily. Our unique and innovative view of the data informs real-time trading decisions and mid-to-long-term investment decisions that keep utility prices low, support the energy transition, and keep the grid running. It’s both challenging work and work with a purpose.   Be a part of our successful, growing business during international transformation.   Position Summary   This role is on the Forecasting Data Science team and combines research with productized model delivery in a forecasting SaaS environment. Based in our Bucharest office, you will partner closely with Forecast Analysts in an operational capacity—managing daily model configurations, runtime monitoring, and exception handling—alongside Product and Engineering teams. You will ensure models are accurate, reliable, and usable in production-grade services, bridging the gap between data exploration and robust operational systems. Position Details   Salary Range: Net 14.000 – 18.000 RON/month Location: Bucharest, Romania Full-time Hybrid - 2 days in the office Reporting to: Engineering Manager   Primary Responsibilities   Build and scale Python-based libraries and pipelines for data extraction, feature engineering, and supervised learning. Support daily forecasting operations, including runtime monitoring, exception handling, and model configuration. Collaborate with Engineering to ensure robust handoff of research models into production systems. Independently tackle moderately complex problems using data patterns to pinpoint root causes. Design and implement scalable, well-reasoned solutions that consider the business impact on power market participants. Participate in research and development to improve model accuracy in a forecasting SaaS environment. Communicate technical workflows and performance metrics clearly to stakeholders and cross-functional partners. Document model methodologies and operational workflows to maintain high standards of system reliability.   Minimum Qualifications   3+ years of professional experience in data science, specifically focused on predictive modeling or forecasting. Master’s degree in a quantitative field (e.g., Statistics, Mathematics, Data Science, or Computer Science). Advanced proficiency in Python and SQL for data manipulation and model development. Demonstrated experience with machine learning frameworks and production-grade data pipelines. Ability to work effectively in an operational capacity, managing real-time model performance and troubleshooting. Preferred Qualifications & Key Competencies   Problem Solving: Independently solves moderately complex problems by ...