Duquesne Light Company, headquartered in downtown Pittsburgh, is a leader in providing electric energy and has been in the forefront of the electric energy market, with a history rooted in technological innovation and superior customer service. Today, the company continues its role as a leader in the transmission and distribution of electric energy, providing a secure supply of reliable power to more than half a million customers in southwestern Pennsylvania.
Duquesne Light Company is committed to creating a culture of inclusion. We value and respect the unique differences and experiences of our employees. We believe that our differences lead to better collaboration, innovation and outcomes. We want you to join our team!
Summary: The Lead Analyst, Data & Analytics, sits within Duquesne Light Company’s (DLC) Corporate Strategy organization, which is guided by the DLC Executive Team to identify and advance ideas that improve efficiency and create enterprise value. The Lead Analyst will perform independent and expert analysis to inform and drive DLC’s on-going efforts to be a data-driven organization. Reporting to the Senior Manager, Analytics Center of Excellence (ACE), the Lead Analyst will be a pivotal team member in finding sustainable efficiency and savings opportunities by rigorously and objectively analyzing enterprise data. This team member will also have responsibility for developing relationships and effective partnerships with all parts of the organization to drive the best enterprise-wide outcomes.
Location: Hybrid, Pittsburgh, PA (Nova Place)
Responsibilities
- Lead end-to-end analytical projects, aligning stakeholders on problem definition, approach, timelines, and decision points.
- Develop business briefs that define scope, goals, requirements, and assumptions.
- Create and maintain project plans that define data collection, evaluation, refinement, and analysis of data.
- Perform advanced data collection, preparation, and quality validation using tools such as Databricks, SQL Server, Snowflake, Excel, RStudio, and Python (Anaconda).
- Select, develop, and apply appropriate analytical and data models to the business use case, balancing rigor and interpretability.
- Turn complex findings into clear narratives and actionable insights, communicating with a wide variety of audiences including executive leadership.
- Document data processes, decisions, and outcomes to support reproducibility, auditability, and organizational knowledge sharing.
- Proactively identify and prioritize analytics opportunities aligned to strategic priorities.
- Champion data governance and stewardship best practices by defining, modeling, and reinforcing standards for data qua