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Lead Analyst, Data & AnalyticsDuquesne Light • United States
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Lead Analyst, Data & Analytics

Duquesne Light
  • US
    United States
  • US
    United States
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Über

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 quality, definitions, and appropriate use. Advance data literacy by coaching partners on analytic thinking, developing tools, and promoting self-service where appropriate. Influence the advancement of a data-driven culture at DLC through continuous improvement of analytical processes, tools, and ways of working.
Additional Responsibilities: Perform other job-related duties as assigned. Storm team duties as assigned.
Education and Experience Required: Bachelor's degree in quantitative field or equivalent experience required. 7+ years of related experience inclusive of aggregating and analyzing large-scale data to create insights required. Combination of proven experience and subject matter expertise in data and analytics required. Experience with SQL, R, Python, or another programming language required.
Preferred Qualifications: Master's degree or relevant certification is a plus.
Skills/Abilities: Strong data-driven analytical skills with an ability to integrate data from multiple sources for the development of actionable, value-add insights and solutions. Demonstrated quantitative and statistical analysis skills including multivariate regression and other advanced statistical analysis such as logistic regression, KNN clustering, time-series analysis, etc. Possesses a strong business acumen, understanding the intersection of financial, operational and customer domains to drive business value. Understanding and awareness of the regulatory environment. Ability to engage cross-functional stakeholders, interpret business challenges, and clearly communicate analyses in terms of business drivers. Ability to plan and effectively manage schedules, balance long-term projects with ad hoc requests, and adapt to changes in prioritization.
Storm Roles All Non-Union Employees will serve in storm roles as appropriate to their role and skillset. EQUAL OPPORTUNITY EMPLOYER
Duquesne Light Holdings is committed to providing equal employment opportunity to all people in all aspects of the employment relationship, without discrimination because of race, age, sex, color, religion, national origin, disability, sexual orientation and gender identity or status as a Vietnam era or special disabled veteran or any other unlawful basis, as defined by applicable law, and fostering a workplace free of unlawful discrimination and retaliation. This policy affects decisions including, but not limited to, hiring, compensation, benefits, terms and conditions of employment, opportunities for promotion, transfer, layoffs, return from a layoff, training and development, and other privileges of employment. An integral part of Duquesne Light Holdings' commitment is to comply with all applicable federal, state and local laws concerning equal employment and affirmative action. Duquesne Light Holdings is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful. If you need a reasonable accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us at HR@duqlight.com and describe the specific accommodation requested for a disability-related limitation.
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