Associate Data Scientist — Energy AI & Analytics

ComEd; Oakbrook Terrace (IL); On-site; USD 59,000 - 81,000; Full time

Benefits offered by this job

Annual salary range

Annual bonus

401(k) match

Medical, dental and vision insurance

PTO and leave options

Job summary

Exelon is seeking a data scientist to develop predictive models and provide analytics support across business units in Illinois. The role focuses on applying machine learning, statistical modeling, and data visualization to improve operations and customer experience.

You will collaborate with data engineers, IT, and business partners, leveraging Python, SQL, Spark, and Azure. Extended hours may be required during storms or energy emergencies.

Qualifications

• Degree in a quantitative field (Bachelor's or Master’s).
• Internship or work in data science with large datasets.
• Knowledge in at least two areas: ML, AI, statistical modeling, data mining, information retrieval, or data visualization.
• Experience with analytics platforms and Python, SQL; familiarity with Spark or Dask.

Responsibilities

• Develop predictive models to improve customer experience and operations.
• Analyze data with modern analytics frameworks (Python, R, Scala); Spark/Hadoop.
• Access and analyze data from Company systems; support strategic plans.
• Provide analytics support to multiple business units.
• Enrich data warehouses and maintain HPC systems.

Skills

Machine learning

Statistical modeling

Data visualization

Python

SQL

Communication skills

Education

Bachelor's or Master’s degree in Quantitative field

Tools

MS Azure

Python

SQL

Spark

Dask

Job description

Exelon is seeking a data scientist to develop predictive models and provide analytics support across business units in Illinois. The role focuses on applying machine learning, statistical modeling, and data visualization to improve operations and customer experience.

You will collaborate with data engineers, IT, and business partners, leveraging Python, SQL, Spark, and Azure. Extended hours may be required during storms or energy emergencies.