Verse is a company focused on managing complex power portfolios for the world's largest energy buyers. They are seeking a Senior Data Scientist to lead the development and deployment of advanced data-driven solutions, leveraging machine learning techniques and supporting optimization modeling infrastructure.
Responsibilities:
- Lead End-to-End Data Science Projects: Own and drive large projects from problem definition through scoping, modeling, validation, and production deployment. Translate business problems into scalable, high-impact modeling solutions with minimal oversight
- Statistical & Machine Learning Modeling: Design, develop, and refine statistical and machine learning models (e.g., time series forecasting, probabilistic models, optimization-linked models) to support decision-making and enhance product capabilities
- Analytics Engineering & Data Modeling: Perform complex data transformations and develop well-structured analytical data models. Translate business and analytical requirements into scalable, tested, and well-documented datasets, with an emphasis on dimensional modeling and reproducibility (e.g., dbt-style workflows)
- Software Development & Productionization: Write clean, efficient, and maintainable Python code. Contribute to integrating models into production systems and model deployment pipelines in a cloud-based environment
- Exploratory Data Analysis & Insight Generation: Apply statistical methods and data exploration techniques to uncover insights, validate assumptions, and inform modeling approaches
- Machine Learning and MLOps: Contribute to Verse’s machine learning modeling infrastructure to support scaling of ML models and improving reliability, monitoring, and performance in production
- Cross-Functional Collaboration: Partner with product, engineering, and business stakeholders to ensure models and insights are aligned with user needs and effectively integrated into workflows
- Technical Leadership: Mentor junior team members, contribute to best practices, and help shape the technical direction of modeling and analytics across the team