Data Scientist

Work from anywhere while tackling complex analytical challenges in a digitally enabled energy environment. Contribute to data-driven decisions that influence millions of customers. Enjoy the flexibility of a remote role with the scale and resources of a large, established organization. Primary Services is excited to announce the role of Data Scientist for a major enterprise client operating at national scale within the energy sector. This opportunity supports a highly visible analytics function where data science is central to financial performance and strategic decision-making. The Data Scientist will grow technical depth through hands-on modeling and analytics while partnering closely with business stakeholders across the organization. Responsibilities • Process and analyze large, complex datasets using Python-based analytics and distributed data processing frameworks. • Build, validate, and maintain statistical and machine learning models supporting customer and prospect insights. • Develop dashboards and analytical outputs that translate data into actionable business intelligence. • Perform hands-on analytics while continuously learning domain-specific applications of data science. • Support business partners by delivering insights that improve profitability, forecasting, and customer experience. • Apply quantitative methods to solve problems related to optimization, prediction, and decision support. Qualifications • 0–3 years of experience in data analysis, data science, or a related quantitative field. • Master’s degree in a quantitative discipline such as statistics, mathematics, economics, computer science, or equivalent practical experience. • Proficiency in Python and common data science libraries used for analysis and modeling. • Experience with statistical software and database query languages. • Working knowledge of machine learning, statistical modeling, or forecasting techniques. • Experience reading from and writing to cloud-based data environments. • Familiarity with version control systems. • Doctoral degree in a quantitative discipline preferred. • Exposure to advanced methods including Bayesian statistics, causal inference, optimization, or natural language processing preferred.