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Sr Data Scientist

Exelon

OAKBROOK TERRACE, ILJob$104–143K/yrSeen 2w agoSeen in employer's feed 3 days ago

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At a glance

Compensation
$104–143K/yr
Location
OAKBROOK TERRACE, IL
Work Authorization
Not specified

Olive lists jobs from US employers, including remote roles you can work from the United States.

Requirements

Credentials this posting asks for.

Bachelor's degree

Job overview

The Senior Data Scientist applies statistical and machine learning methods to complex data, developing insights that inform business decisions and improve customer experience, operations, and safety. The role collaborates with business, engineering, and technology stakeholders, supports strategic planning, and communicates findings and recommendations. It also contributes to data preparation, analytics solutions, and the development and deployment of predictive models.

Skills & qualifications

RequiredNice to have

Skills

Machine LearningArtificial IntelligenceStatistical ModelingData MiningInformation RetrievalData VisualizationPythonRScalaOpen SourceUnixCommunicationStatisticsProbability TheoryOptimizationCausal InferenceNatural Language ProcessingData StructuresAlgorithmsModel ValidationResponsible AISQLRelational Data PlatformsColumnar Data PlatformsCloud Data PlatformsLakehouse PlatformsBig Data PlatformsReproducible WorkflowsData QueryingData JoiningPresentationStorytellingFacilitationTime ManagementStakeholder Engagement

Qualifications

Bachelor's in Quantitative Discipline4+ Years Relevant ExperienceMaster's in Quantitative DisciplinePhD in Quantitative Discipline

Benefits

401(k) Match
Medical Insurance
Dental Insurance
Vision Insurance
Paid Time Off
Parental Leave
Tuition Assistance

Full job description

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.

Are you on for the challenge?

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.

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.

  • Annual Bonus for eligible positions: 15%

  • 401(k) match and annual company contribution

  • Medical, dental and vision insurance

  • Life and disability insurance

  • Generous paid time off options, including vacation, sick time, floating and fixed holidays, maternity leave and bonding/primary caregiver leave or parental leave

  • Employee Assistance Program and resources for mental and emotional support

  • Wellbeing programs such as tuition reimbursement, adoption and surrogacy assistance and fitness reimbursement

  • Referral bonus program

  • And much more

Note: Exelon-sponsored compensation and benefit programs may vary or not apply based on length of service, job grade, job classification or represented status. Eligibility will be determined by the written plan or program documents.

Exelon is proud to be an equal opportunity employer and employees or applicants will receive consideration for employment without regard to: age, color, disability, gender, national origin, race, religion, sexual orientation, gender identity, protected veteran status, or any other classification protected by federal, state, or local law. If you are an individual with a disability and need an accommodation to complete the application, please email us at [email protected].

How this job compares

Set against the 4,830 open Data Scientist jobs on Olive Jobs, counted November 3, 2026.

Pay
  • This posting$104–143K/yr
  • Illinois median$120–187K/yr119 salary ranges
  • US median$135–213K/yr3,705 salary ranges

This range's midpoint, $124K, is 22% below the Illinois median midpoint ($158K) — in the lowest quarter of Data Scientist salary ranges in Illinois.

Openings
Olive Jobs lists 140 open Data Scientist jobs in Illinois and 4,830 across the US. 6% of them nationwide are listed as remote or flexible.
Hiring the most in Illinois
Experience
This posting asks for at least 4 years of experience; Data Scientist postings that state a minimum ask for 5 years at the median (4,140 postings).
Education
This posting asks for a bachelor's degree; 2,278 of the 4,830 open Data Scientist jobs (47%) ask for a bachelor's degree or higher.

Counted across the open, public US postings on Olive Jobs on November 3, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.

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