✦ Luna Orbit — Data & Analytics

Sr Data Scientist

at Exelon

📍 PHILADELPHIA, Pennsylvania, United States Unknown 💰 $104K – $104K USD / year Posted March 28, 2026
Salary $104K – $104K USD / year
Type Not Specified
Experience mid
Exp. Years Not specified
Education Not specified
Category Data & Analytics

This role involves applying data science techniques to energy data, developing predictive models, and extracting insights to support energy transformation initiatives.

  • Extract insights from energy data
  • Develop predictive models
  • Handle unstructured data
  • Standardize and cleanse data
  • Collaborate with stakeholders

The technical environment includes machine learning, statistical analysis, big data platforms, Python, R, and SQL, with a focus on large-scale energy datasets.

The ideal candidate is a mid-level data scientist with expertise in machine learning, statistical modeling, and big data analysis. They should be proficient in Python and SQL, with experience handling large datasets and unstructured data, and possess strong collaboration skills.

Data analysisMachine learningStatistical modelingData miningData cleansingData standardization
IoTTime-series analysisBig Data platformsCloud platformsAI frameworks
PythonRSQLBig DataData Warehousing
Data ScienceMachine LearningStatisticsData MiningData AnalysisPredictive ModelingBig DataPythonSQL
Data ScienceMachine LearningStatisticsData MiningData ManipulationTime-SeriesRelational DataUnstructured DataBig DataPetabytesPythonRSQLData CleansingData StandardizationPredictive ModelingAIDeep Learning
collaborationcommunicationproblem-solvinganalytical thinkingcontinuous learning
Industry Energy
Job Function Data analysis and modeling for energy sector
Role Subtype Data Scientist
Tech Domains Python, R, SQL, Big Data
data scientistmachine learningstatisticsdata miningdata analysispredictive modelingbig datapetabytespythonsqldata cleansingdata standardizationdata manipulationrelational dataunstructured dataiottime-seriescloud platformsai frameworksstatistical modeling

Lack of experience with machine learning or data mining, No proficiency in Python or SQL, Inability to work with big data or petabyte-scale datasets

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