Data Scientist

PSEG•Newark, NJ

1d•Hybrid

About The Position

PSEG is seeking a Data Scientist to transform raw data into actionable insights that support strategic decisions across the organization. Working with cross-functional teams in Customer Analytics and IT, the role develops analytics solutions, including AI/ML models, for Customer Solutions; identifies friction points in customer journeys; analyzes customer behavior; and helps improve customer experience. The position also presents analysis and recommendations to management. The role uses data from multiple sources to create insights and data products, improve data pipelines and data quality, and apply statistical analysis and data mining to operational and non-operational data. It supports business adoption of technology solutions and requires communicating findings to technical and non-technical stakeholders. This is a hybrid position, with at least three onsite days per week. PSEG is not offering visa sponsorship. During emergency restoration efforts, employees may be required to perform duties outside their routine responsibilities and work a schedule different from normal operations.

Requirements

Bachelor’s degree in data science, engineering, computer science, information technology, information systems, statistics, or a related field.
2–5 years of knowledge and experience with data mining techniques, data modeling, statistical analysis, and algorithms.
2–5 years of experience using query languages such as SQL and developing and maintaining ETL workflows using SQL Server Integration Services (SSIS).
2–5 years of experience leveraging AWS services to deploy scalable data pipelines and analytics solutions.
2–5 years of experience using Python for analytics, SQL modeling, and AI/ML model development.
2–5 years of experience in data visualization using Power BI and/or other data visualization software.
Experience developing business requirements and testing plans with business stakeholders, IT, and vendors.
Attention to detail and experience working with large data sets.
Excellent verbal and written communication skills, including the ability to explain technical concepts clearly and succinctly to non-technical stakeholders.
Ability to synthesize analysis into PowerPoint presentations for management, including recommendations and actionable insights.
Results-oriented, data-driven, and self-starting approach.
Compliance with the Department of Energy’s regulation 10 CFR 810 is required.

Nice To Haves

Advanced degree, such as a master’s degree in data science, data analytics, engineering, computer science, information technology, information systems, statistics, or a related field.
Familiarity with data governance, data quality, and responsible AI practices.
AWS and/or Power BI certifications.
Exposure to emerging technologies such as generative AI, large language models (LLMs), or retrieval-augmented generation (RAG).
Experience with call center and collections operational metrics.

Responsibilities

Collect, summarize, analyze, and deliver insights and data products using data from multiple sources.
Identify valuable data sources and assist in optimizing data pipelines to ensure data quality, integrity, and security.
Transform data to uncover patterns and trends and define analytics solutions, including AI/ML solutions, to support customer-experience initiatives.
Analyze operational and non-operational data to deliver insights that contribute to improvements.
Apply statistical analysis and data mining techniques to validate assumptions and build scenarios.
Interpret data to discover solutions, identify opportunities, and support decision-making.
Communicate results and insights to subject matter experts and cross-functional teams.
Support business adoption of technology solutions.
Develop PowerPoint presentations that summarize analysis, recommendations, and actionable insights for management.