Senior Data Scientist - Energy Analytics

About the Role

Our client is looking for a highly analytical and innovative Senior Data Scientist to join their team in Nottingham , focusing on energy analytics . This role is crucial for extracting valuable insights from vast datasets related to energy consumption, production, and market trends. You will develop predictive models, build data pipelines, and communicate complex findings to stakeholders to drive strategic decision-making and optimize energy operations. This is an exciting opportunity to work with cutting-edge technologies and contribute to shaping the future of the energy industry through data-driven intelligence.

Key Responsibilities

• Design, develop, and implement machine learning models and algorithms for energy analytics , forecasting, and optimization.
• Clean, transform, and analyze large, complex datasets from various energy sources and systems.
• Develop data visualizations and dashboards to effectively communicate insights to technical and non-technical audiences.
• Collaborate with domain experts in engineering, operations, and market analysis to identify key business questions and data-driven solutions.
• Build and maintain robust data pipelines and ETL processes for model training and deployment.
• Stay abreast of the latest advancements in data science , machine learning, and artificial intelligence in the energy sector.

Requirements

• Master's or Ph.D. in Data Science, Computer Science, Statistics, or a related quantitative field.
• Minimum of 7 years of experience in data science and machine learning, with a focus on the energy sector .
• Proficiency in programming languages such as Python or R, and experience with relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Strong experience with SQL and database management, as well as big data technologies (e.g., Spark, Hadoop).
• Demonstrated ability to develop and deploy machine learning models in production environments.
• Excellent communication, presentation, and problem-solving skills.

Benefits

• Competitive salary and bonus structure.
• Hybrid working model offering excellent flexibility.
• Comprehensive health, dental, and vision insurance.
• Retirement savings plan with employer match.
• Opportunities for professional development, attending conferences, and continuous learning in data analytics .