Sr Data Scientist

About Us

As the largest private-sector power producer in the world and the nation's largest producer of clean and reliable energy, Constellation is focused on our purpose: lighting the way to a brilliant tomorrow for all. We have been the leader in clean energy production for more than a decade and are cultivating a workplace where employees can grow, thrive, and contribute. Our portfolio includes 55 gigawatts of capacity from nuclear, natural gas, geothermal, hydro, wind, and solar facilities, powering the equivalent of 27 million homes. Our culture and employee experience are powered by passion and purpose, driving healthier communities and a cleaner planet.

About the Role

Apply the appropriate data science or analytical methods to extract knowledge and insights from data, which may include time-series (power plant equipment data, environmental data, or other), structured (relational data stores), and unstructured (text and multimedia) datasets. Collaborate closely with internal stakeholders, information architects, data engineers, project/program managers, and other teams to turn data into critical information for decision-making. This involves understanding business needs, providing and receiving feedback, and planning the transfer of developed solutions.

Responsibilities

• Mine big and small data for insights using advanced statistical and machine learning methods.
• Validate findings with the business by sharing analysis outputs in a way that can be understood by business stakeholders.
• Serve as a subject matter expert in 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, business stakeholders, and IT partners.
• Collect, cleanse, standardize, and analyze data from a variety of internal and external sources.
• Produce novel insights to inform business actions using statistical modeling and machine learning techniques on complex datasets (terabytes or petabytes).
• Develop key predictive models to reduce overall annual expenses for nuclear, improve performance, and optimize specific performance criteria.
• Recommend data sampling techniques, data collection, and data cleaning specifications and approaches.
• Apply missing data treatments as needed.
• Analyze data using advanced analytics techniques in modern frameworks (Python, R, Scala, Spark, Hadoop, etc.).
• Access and analyze data sourced from various company systems of record.
• Support the development of strategic business 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.
• Work with stakeholders and subject matter experts to understand business needs, goals, and objectives.
• Collaborate with business, engineering, and technology teams to develop solutions for data-intensive business problems.
• Translate business problems into data science projects.
• Collaborate with other analytic teams across Exelon on big data analytics techniques and tools to improve analytical capabilities.

Requirements

• Bachelor's degree in a quantitative discipline (e.g., Data Science, Data Analytics, Applied Mathematics, Statistics, Computer Science, Operations Research, or related field).
• 5-8 years of relevant experience developing hypotheses, applying machine learning algorithms, validating results to analyze large datasets, and extracting actionable insights.
• Previous research or professional experience applying advanced analytic techniques to large, complex datasets.
• Strong knowledge in at least two of the following areas: machine learning, artificial intelligence, statistical modeling, data mining, information retrieval, or data visualization.
• Proven experience in developing and deploying predictive analytics projects using one or more leading languages (Python, R, Scala, etc.).
• Ability to translate data analysis and findings into coherent conclusions and actionable recommendations for business partners, practice leaders, and executives.
• Strong oral and written communication skills.

Preferred Qualifications

• Proven experience in Python-based data science, including ML model development, generative AI (LLMs), prompt engineering, and end-to-end pipeline automation with tools like Databricks and Azure Data Factory.
• Master’s or PhD in a quantitative discipline.
• Prior exposure to data structures related to power-generating plant equipment and systems, as well as organizational performance data in the nuclear power industry.
• Prior exposure to the nuclear, power generation, or broader energy sector.
• Prior exposure to the full spectrum of the data science lifecycle, including data acquisition, maintenance, processing, analysis, and communication.
• Solid understanding of relevant theories in machine learning, statistics, probability theory, data structures, algorithms, and optimization.
• Expert-level coding skills (Python, R, Scala, SQL, etc.).
• Proficiency in database management and large datasets: create, edit, update, join, append, and query data from columnar and big data platforms.
• Ability to translate executive and analytics leaders' vision and guidance into methods and analytics.
• Strong time management and presentation skills.

Benefits

• Competitive compensation, including a bonus program and 401(k) with company match.
• Employee stock purchase program.
• Comprehensive medical, dental, and vision benefits, including robust wellbeing programs.
• Disability and life insurance benefits.
• Paid time off for vacation, holidays, and sick days.
• Additional benefits and rewards to support employees and their families.

Pay

Expected salary range of $130,500 to $145,000, varying based on experience, along with a comprehensive benefits package that includes a bonus and 401(k).