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Sr Data Scientist

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Location: BALTIMORE, MD, United States
Organization: Baltimore Gas & Electric Co
Job ID: 253361
Remote Work: No Remote
Date Posted: May 25, 2024

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Job Description


We're powering a cleaner, brighter future.

Exelon is leading the energy transformation, and we're calling all problem solvers, innovators, community builders and change makers. Work with us to deliver solutions that make our diverse cities and communities stronger, healthier and more resilient.

We're powered by purpose-driven people like you who believe in being inclusive and creative, and value safety, innovation, integrity and community service. We are a Fortune 200 company, 19,000 colleagues strong serving more than 10 million customers at six energy companies -- 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).

In our relentless pursuit of excellence, we elevate diverse voices, fresh perspectives and bold thinking. And since we know transforming the future of energy is hard work, we provide competitive compensation, incentives, excellent benefits and the opportunity to build a rewarding career.

Are you in?


Are you passionate about leveraging artificial intelligence to drive innovation in the utility industry? Join our fast growing and impactful Advanced Data Science and Intelligence Team at BGE as an AI centric Data Scientist and play a pivotal role in shaping the future of energy delivery. As part of our organization, you’ll analyze vast datasets, develop predictive models, and uncover valuable insights that enhance grid efficiency, customer experiences, and sustainability. If you thrive on solving complex challenges and want to contribute to a safe, clean, reliable, and smarter energy landscape, this opportunity is tailor-made for you! 

We’re looking with someone with deep experience in:

  • Machine Learning (ML) Algorithms: Proficiency in designing, implementing, and fine-tuning ML models. Familiarity with regression, classification, clustering, and recommendation algorithms.
  • Deep Learning: Experience with neural networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and other deep learning architectures. Ability to work with frameworks like TensorFlow or PyTorch.
  • Natural Language Processing (NLP): Understanding of NLP techniques for text analysis, sentiment analysis, named entity recognition, and language modeling. Knowledge of pre-trained language models (e.g., BERT, GPT) is a plus.


  • 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.
  • 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 
  • Access and analyze data sourced from various Company systems of record. Support the development of strategic business, marketing, and program implementation plans. 
  • Access and enrich data warehouses across multiple Company departments. Build, modify, monitor and maintain high-performance computing systems. 
  • Provide expert data and analytics support to multiple business units 
  • 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. 


  • 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.



  • 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.


  • Education: Masters, or PhD in a Quantitative discipline. Ex: Applied Mathematics, Computer Science, Finance, Ops Research, Physics, Statistics, or related field
  • Experience: Prior exposure to data structures pertaining to smart-meters, billing, or outage management systems. Prior exposure to the utilities or broader energy sector. Prior exposure to the full spectrum of data science lifecycle, including data acquisition, maintenance, processing, analysis, and communication.
  • Analytic Abilities: Solid understanding of relevant theories in machine learning, statistics, probability theory, data structures and algorithms, optimization, etc.
  • Technical Knowledge: Expert level coding skills (Python, R, Scala, SQL, etc), and experience developing in a Unix environment. Proficiency in database management and large datasets: create, edit, update, join, append and query data from columnar and big data platforms.
  • Communication Skills: Ability to translate executive and analytics leaders' vision and guidance into methods and analytics. Strong time management and presentation skills.

  • Annual salary will vary based on a candidate's skills, qualifications, experience, and other factors: $104,000-$156,000
  • Annual bonus and incentive pay up to 15%
  • 401(k) match and annual company contribution
  • Medical, Dental and Vision Insurance
  • Life and disability insurance
  • Generous paid time off, including vacation, floating and fixed holidays and sick time
  • Maternity leave as well as paid bonding/primary caregiver leave or parental leave for the birth or adoption of a child or to care for an ill family member, as applicable (eligibility based on position)
  • Long Term Incentive Plan for eligible positions
  • Wellbeing programs such as tuition reimbursement, adoption assistance and fitness reimbursement
  • Referral bonus program
  • And much more
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