Senior Data Scientist Why YOU want this position At Enverus, we’re committed to empowering the global quality of life by helping our customers make energy affordable and accessible to the world.  We are the most trusted energy-dedicated SaaS company, with a platform built to maximize value from generative AI, and our innovative solutions are reshaping the way energy is consumed and managed. By offering anytime, anywhere access to analytics and insights, we’re helping our customers make better decisions that help provide communities around the world with clean, affordable energy. The energy industry is changing fast. But we’ve continued to lead the way in energy technology, creating intelligent connections across the entire energy ecosystem, from renewables, power and utilities, to oil and gas and financial institutions. Our solutions create more efficient production and distribution, capital allocation, renewable energy development, investment and sourcing, and help reduce costs by automating crucial business operations. Of course, this wouldn’t be possible without our people, which is why we have built a team of individuals from a diverse range of backgrounds.  Are you ready to help power the global quality of life? Join Enverus, and be a part of creating a brighter, more sustainable tomorrow.We are currently seeking a highly driven Senior Data Scientist based in Canada with experience or interest in power markets and congestion to join our data science team. This role offers the opportunity to work at a rapidly growing company delivering industry-leading solutions in one of the world’s most dynamic sectors.You will be a key contributor to Enverus’ fastest-growing product line. The team pairs complex algorithms and machine learning with powerful computational infrastructure and an intuitive user interface that is unmatched in the industry. Small, fast-paced, and highly skilled, this group welcomes talented engineers from diverse backgrounds to help shape the future of energy together. This role works closely with engineering and product teams to deliver production-grade machine learning systems used directly by customers.  Performance Objectives  Design, build, deploy and maintain machine learning models supporting core product capabilitiesPrototype, evaluate and productionize models using Python and modern ML frameworksOwn individual models end-to-end, from development through monitoring and iterationDeploy models into cloud-native and containerized environmentsBuild and maintain scalable training and inference workflowsMonitor production model performance using metrics, alerts and dashboardsAnalyze model performance, design experiments and drive continuous improvementPerform and lead feature engineering on large, complex datasets from multiple sourcesWork with large datasets using SQL and analytical data toolsExtend and maintain data ingestion and scraping platforms supporting model training and inferenceCollaborate closely with software engineering and product teams to align models with customer needsParticipate in operational support related to data pipelines or production models, as needed.Participate in technical design discussions, code reviews and data science best practicesCommunicate findings, tradeoffs and recommendations clearly to both technical and non-technical stakeholders Competitive Candidate Profile 5+ years of relevant industry or research experience in data science or machine learningBachelor’s degree in a quantitative field such as Data Science, Computer Science, Mathematics, Software Engineering or related disciplineStrong proficiency in Python, including experience with:scikit-learnPyTorchSolid understanding of machine learning fundamentals, including supervised and unsupervised learning, model evaluation and feature engineeringExperience developing predictive models and taking them through the full model lifecycleAbility to write well-documented experiments and production-ready codeExperience supporting models in production environmentsFamiliarity with containerization and orchestration technologiesStrong SQL skillsAbility to develop reports and visualizations for internal teamsDesired Qualifications Familiarity with energy marketsExperience with GCP and/or AWSExperience with time-series modeling or forecastingExperience working with streaming data and event-driven systemsExperience with Snowflake, Databricks or similar cloud data warehousesData engineering experience or experience building data pipelinesExperience using infrastructure-as-code tools such as Terraform or Pulumi