This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Scientist based in the Canada. This role offers the opportunity to apply advanced data science, machine learning, and AI techniques to solve complex challenges in the energy sector. As a Senior Data Scientist, you will work with one of the largest energy datasets available, combining large-scale meter data, weather information, geospatial context, and grid attributes. You will develop production-ready analytics that support smarter energy decisions, improve grid reliability, and accelerate the transition toward a more sustainable future. The position blends deep technical expertise with real-world impact, allowing you to build models used by utilities, regulators, and industry stakeholders. You will collaborate with data scientists, engineers, and domain experts to transform complex data into actionable solutions. This is a remote opportunity for an experienced professional passionate about applying AI and analytics to meaningful infrastructure challenges. \n

Accountabilities: As a Senior Data Scientist, you will lead the development of advanced analytical solutions that combine statistical modeling, machine learning, and AI to improve energy resource management and deliver scalable platform capabilities. Lead the design, development, and refinement of statistical and machine learning models for load forecasting, flexibility analysis, customer behavior modeling, and energy resource optimization. Analyze large-scale datasets, including smart meter data, customer information, grid attributes, and external factors, to identify patterns and support strategic decision-making. Select and apply appropriate statistical, machine learning, or deep learning approaches based on business needs and analytical challenges. Improve existing models while developing new predictive capabilities that can be deployed in production environments. Validate models through structured testing methods, including backtesting, cross-validation, and uncertainty analysis. Collaborate with data scientists, engineers, and energy domain experts to ensure analytical solutions accurately reflect real-world conditions. Translate complex customer requirements and industry challenges into reusable data products and platform capabilities. Develop clean, efficient, maintainable code and create clear documentation to support reproducibility and scalability. Communicate analytical assumptions, limitations, and insights effectively to both technical and non-technical stakeholders. Support customer-facing initiatives by applying data science expertise to practical energy and grid-related challenges. Requirements: The ideal candidate combines strong data science expertise, production engineering skills, and the ability to apply advanced analytics to complex real-world systems. 5–8+ years of relevant data science experience after completing a Bachelor’s degree, with the ability to independently lead complex analytical projects. Strong expertise in supervised and unsupervised machine learning techniques and statistical modeling approaches. Experience applying data science to energy systems, demand response, energy efficiency, distributed energy resources, utility operations, or other complex physical systems. Advanced proficiency in Python and SQL, with experience building clean, production-ready data solutions. Strong experience with Python data science libraries such as pandas, NumPy, SciPy, and scikit-learn. Experience working with time-series data, panel data analysis, and predictive modeling. Strong data visualization skills and ability to communicate analytical findings clearly. Experience translating customer needs into technical solutions or production software capabilities. Solid understanding of statistics, uncertainty analysis, causal reasoning, and analytical best practices. Ability to collaborate effectively with technical teams and influence cross-functional stakeholders. Strong communication skills with the ability to explain complex concepts to diverse audiences. Ability to balance analytical rigor with practical engineering considerations. Preferred experience with neural networks, PyTorch, TensorFlow, sequence modeling, deep learning for time series, geospatial analysis, distributed energy resource data, or advanced ML workflows. Advanced degree in engineering, physics, mathematics, or another technical discipline is a plus. Benefits: Competitive full-time compensation package. Fully remote work opportunity for candidates based in the United States or Canada. Opportunity to work with large-scale, real-world datasets and advanced machine learning challenges. Ability to contribute to solutions supporting energy affordability, reliability, and sustainability. Collaborative environment with experienced data scientists, engineers, and industry experts. Opportunity to build production-level analytics used by utilities, regulators, and energy stakeholders. Work on impactful projects addressing major infrastructure and environmental challenges.

\n How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1