Senior Data Scientist - Energy Analytics

About the Role

Our client is looking for an accomplished Senior Data Scientist to lead their advanced analytics initiatives within the energy sector, operating remotely. This position involves leveraging vast datasets to uncover insights, develop predictive models, and drive data-informed decision-making across exploration, production, and distribution. You will work with cutting-edge technologies and collaborate with cross-functional teams to solve complex business challenges. This role offers a unique opportunity to make a substantial impact on the company's strategic direction through sophisticated data analysis and interpretation in a fully remote setting.

• Develop and deploy machine learning models for forecasting, anomaly detection, and optimization in energy operations .
• Analyze large, complex datasets to identify trends, patterns, and actionable insights.
• Design and implement A/B testing frameworks to evaluate the effectiveness of new strategies.
• Collaborate with engineers and business stakeholders to define analytical requirements and deliver solutions.
• Communicate complex findings and recommendations clearly to both technical and non-technical audiences.
• Mentor junior data scientists and contribute to the team's technical growth and best practices.

• Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field.
• 5+ years of experience in data science and machine learning, with a focus on predictive modeling.
• Proficiency in programming languages such as Python or R, and libraries like Tensor Flow, PyTorch, or scikit-learn.
• Strong experience with SQL and big data technologies (e.g., Spark, Hadoop).
• Expertise in statistical analysis, experimental design, and data visualization .
• Excellent problem-solving skills and the ability to work independently in a remote environment.

• Highly competitive salary and comprehensive bonus structure.
• Exceptional health, dental, and vision insurance coverage.
• Significant professional development budget for conferences and courses.
• Opportunity to work on challenging and impactful data science projects in the energy domain.
• A fully remote work environment that promotes autonomy and work-life balance.