Sr Data Scientist

Exelon; Chicago (IL); Hybrid; USD 104,000 - 143,000; Full time

Benefits offered by this job

Competitive benefits

Job summary

Exelon is seeking a Sr Data Scientist in the Operations team, based in Oak Brook Terrace, Illinois. The role is hybrid, requiring collaboration with ComEd and other divisions to extract insights from terabyte-scale datasets using advanced ML techniques.

You will develop predictive models, apply data mining and statistical methods, and translate findings into strategic actions for energy delivery and customer operations. A strong background in Python/R/Scala and big data tools is essential.

Qualifications

• Education: Bachelor's degree in a quantitative discipline; Master’s/PhD preferred.
• 4-7 years of experience applying ML techniques to large datasets.
• Strong ability to translate analysis into actionable business recommendations.

Responsibilities

• Develop predictive models to improve customer experience and operations.
• Analyze data with Python, R, Scala, or equivalent; use Spark/Hadoop as needed.
• Collaborate with stakeholders to translate business needs into data science projects.
• Support multiple business units with expert data analytics.

Skills

Machine learning

Statistical modeling

Data mining

Data visualization

Artificial intelligence

Education

Bachelor's degree in a quantitative discipline

Master’s degree or PhD in a quantitative discipline

Tools

Python

R

Scala

SQL

Unix

Job description

Sr Data Scientist

Operations

OAKBROOK TERRACE, Illinois

Hybrid

ComEd

30488

10/15/2026

Who We Are

Exelon is helping build a more affordable, reliable energy future for the communities we serve. We’re looking for people who are ready to make a difference and work together to deliver the energy our customers count on every day.

As a Fortune 200 company and one of the nation's largest utility companies, we have more than 20,000 colleagues who serve nearly 11 million customers through six fully regulated utilities - Atlantic City Electric (ACE), Baltimore Gas and Electric (BGE), Commonwealth Edison (ComEd), Delmarva Power & Light (DPL), PECO Energy Company (PECO), and Potomac Electric Power Company (Pepco).

Exelon is built by people who put safety first, work together to solve problems and show up every day for our customers and communities. We believe strong teams are built on trust, respect and a shared commitment to high-performance culture. And our commitment to employees includes creating an environment where people can grow, develop new skills and build thriving careers.

We know this work isn’t easy. That’s why we offer competitive compensation, incentives, excellent benefits and the opportunity to build a rewarding career. No matter your role, you will be part of a team that is committed to making a difference, improving how we work and delivering for the people who depend on us.

Primary Purpose

Apply the scientific method to extract knowledge and insights from data, which may take the form of time-series (smart-meters, smart-grid, and other IoT), structured (relational data stores), and unstructured (text and multi-media) data sets. Closely collaborate with various internal stakeholders, information architects, data engineers, project/program managers, and other teams to turn data into critical information to inform decision making. This requires understanding business needs, providing and receiving regular feedback, and planning the proper transfer of developed solutions. Mine big and small data for insights, using advanced statistic and machine learning methods. Validate findings with the business by sharing analysis outputs in a way that can be understood by business stakeholders. Become a subject matter expert in the areas of artificial intelligence, machine learning, feature engineering, data mining, and data manipulation/storage. Demonstrate commitment to continuous learning and professional development in technical subject matter. Share knowledge with team members, and business stakeholders, and IT partners. Collect, cleanse, standardize and analyze data from a variety of internal and external sources. Produce novel insights to help inform business actions using statistical modeling and machine learning techniques on complex data-sets on the order of several terabytes or petabytes. Position may be required to work extended hours for coverage during storms or other energy delivery emergencies.

Are you on for the challenge?

Primary Duties

• Develop key predictive models that lead to delivering a premier customer experience, operating performance improvement, and increased safety best practices.
• Develop and recommend data sampling techniques, data collections, and data cleaning specifications and approaches. Apply missing data treatments as needed. (25%)
• Analyze data using advanced analytics techniques in support of process improvement efforts using modern analytics frameworks, including but not limited to Python, R, Scala, or equivalent; Spark, Hadoop file system and others (15%)
• Access and analyze data sourced from various Company systems of record. Support the development of strategic business, marketing, and program implementation plans. (15%)
• Access and enrich data warehouses across multiple Company departments. Build, modify, monitor and maintain high-performance computing systems. (5%)
• Provide expert data and analytics support to multiple business units (20%)
• Works with stakeholders and subject matter experts to understand business needs, goals and objectives. Work closely with business, engineering, and technology teams to develop solution to data-intensive business problems and translates them into data science projects. Collaborate with other analytic teams across Exelon on big data analytics techniques and tools to improve analytical capabilities. (20%)

Job Scope

Support business unit strategic planning while providing a strategic view on machine learning technologies. Advice and counsel key stakeholders on machine learning findings and recommend courses of action that redirect resources to improve operational performance or assist with overall emerging business issues. Provide key stakeholders with machine learning analyses that best positions the company going forward. Educate key stakeholders on the organizations advance analytics capabilities through internal presentations, training workshops, and publications.

Minimum Qualifications

• Education: Bachelor's degree in a Quantitative discipline. Ex: Applied Mathematics, Computer Science, Finance, Operations Research, Physics, Statistics, or related field.
• 4-7 years of relevant experience developing hypotheses, applying machine learning algorithms, validating results to analyze multi-terabyte datasets and extracting actionable insights is required. Previous research or professional experience applying advanced analytic techniques to large, complex datasets.
• Analytical Abilities: Strong knowledge in at least two of the following areas: machine learning, artificial intelligence, statistical modeling, data mining, information retrieval, or data visualization.
• Technical Knowledge: Proven experience in developing and deploying predictive analytics projects using one or more leading languages (Python, R, Scala, etc.). Experience working within an open source environment and Unix-based OS.
• Communication Skills: Ability to translate data analysis and findings into coherent conclusions and actionable recommendations to business partners, practice leaders, and executives. Strong oral and written communication skills.

Preferred Qualifications

• Education: Master’s degree or PhD in a quantitative discipline such as Applied Mathematics, Computer Science, Data Science, Engineering, Operations Research, Physics, Statistics, or a related field.
• Experience: Experience applying data science to electric utility, energy, industrial, or asset-intensive environments. Exposure to smart meter, grid, outage, maintenance, asset health, inspection, work management, or customer data. Experience supporting the full data science lifecycle, including use case framing, data acquisition, preparation, modeling, validation, communication, deployment support, and ongoing performance monitoring.
• Thrives in complex, data-rich environments. Enjoys learning new and legacy technologies, untangling imperfect data, understanding how information flows through the organization, and building scalable processes that turn data into actionable insights and business value.
• Organizational Agility: The ability to ingest data from a variety of sources, whose age, structure, and data quality will vary. The willingness to consistently seek stakeholder perspective on understanding.
• Analytic Abilities: Strong understanding of machine learning, statistics, probability theory, optimization, causal inference, natural language processing, data structures, algorithms, model validation, and responsible AI practices.
• Technical Knowledge: Advanced coding skills in Python, R, Scala, SQL, or equivalent languages. Experience working with large-scale relational, columnar, cloud, lakehouse, or big data platforms; building reproducible analytics workflows; querying and joining complex data; and partnering with data engineering or technology teams to prepare solutions for operational use.
• Communication Skills: Ability to translate leader and stakeholder priorities into analytical methods, decision-support products, and actionable recommendations. Strong presentation, storytelling, facilitation, time management, and stakeholder engagement skills.

Benefits

• Annual salary will vary based on a candidate’s skills, qualifications, experience, and other factors: $104,000.00/Yr. – $143,000.00/Yr.