Senior Data Scientist - Energy Analytics

About the Role

Our client is seeking a talented and experienced Senior Data Scientist to join their innovative analytics team in Nottingham . This role focuses on leveraging vast datasets to derive actionable insights within the energy sector . You will be responsible for developing advanced analytical models, machine learning algorithms, and predictive tools to optimize energy generation, distribution, consumption, and trading. The ideal candidate possesses strong statistical and programming skills, a deep understanding of data science methodologies, and a passion for applying these skills to solve complex challenges in the energy domain.

Key Responsibilities

• Design, develop, and implement advanced data models and machine learning algorithms to analyze large energy datasets.
• Extract, clean, and transform data from various sources, ensuring data quality and integrity for analysis.
• Develop predictive models for energy demand forecasting, asset performance, and market price prediction.
• Utilize statistical analysis and visualization techniques to uncover trends, patterns, and insights from energy data.
• Collaborate with domain experts, engineers, and business stakeholders to understand their needs and translate them into data science solutions.
• Communicate complex analytical findings and recommendations clearly to both technical and non-technical audiences.
• Stay current with the latest advancements in data science, machine learning, and artificial intelligence relevant to the energy industry.

Requirements

• Master's or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.
• Minimum of 6 years of professional experience as a Data Scientist, with a strong focus on applying analytical techniques to real-world problems.
• Proficiency in programming languages such as Python or R, and extensive experience with relevant libraries (e.g., scikit-learn, TensorFlow, Pandas).
• Strong experience with SQL and database management, as well as big data technologies (e.g., Spark, Hadoop).
• Demonstrated experience in developing and deploying machine learning models in a production environment.
• Excellent understanding of statistical modeling, time series analysis, and data visualization techniques.
• Strong problem-solving skills and the ability to work effectively in a team-oriented, fast-paced environment.

Benefits

• Competitive salary and attractive bonus scheme.
• Hybrid working model providing flexibility and work-life balance.
• Comprehensive health and wellness benefits package.
• Opportunities for continuous learning, professional development, and attending industry conferences.
• Access to cutting-edge technology and a data-rich environment in Nottingham .
• Be a key contributor to optimizing the future of energy through data-driven insights.