Assoc Data Scientist, AI

Constellation Energy Generation, LLC.•Chicago, IL

About The Position

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 we are cultivating a workplace where our employees can grow, thrive, and contribute. Now integrated with Calpine, our portfolio includes 55 gigawatts of capacity from nuclear, natural gas, geothermal, hydro, wind and solar facilities, with the generating capacity to power the equivalent of 27 million homes. Our culture and employee experience make it clear: We are powered by passion and purpose. Together, we're creating healthier communities and a cleaner planet, and our people are the driving force behind our success. At Constellation, you can build a fulfilling career with opportunities to learn, grow and make an impact. By doing our best work and meeting new challenges, we can accomplish great things. Join us in meeting the country's energy needs today and tomorrow. Total Rewards Constellation offers an extensive selection of benefits and rewards to help our employees thrive professionally and personally. We provide competitive compensation and a wide-range of benefits that support both employees and their families, helping them prepare for the future. In addition to highly competitive salaries, eligible employees are offered a bonus program, 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; and much more. Expected salary range of $75,600 to $84,000, varies based on experience, along with comprehensive benefits package that includes bonus and 401(k). Primary Purpose of Position Apply data science, machine learning, and AI methods to extract knowledge and insights from structured, unstructured, and time-series data across the enterprise. Support the development and deployment of predictive models, analytical solutions, and AI-augmented workflows that support data-driven decision-making and operational improvement. Work closely with cross-functional teams including data engineers, solution architects, project managers, and business stakeholders to understand business needs, translate them into data science and AI projects, and deliver actionable insights. Collaborate with enterprise AI and Responsible AI teams to ensure all solutions align with Constellation's AI governance processes, Export Control (ECI) requirements, and Responsible AI principles. Leverage enterprise platforms such as Databricks, Azure AI services, and Azure OpenAI to build, test, and deliver scalable analytical and AI-powered solutions. Support the development and integration of AI capabilities across business functions, including foundational work with large language models (LLMs), retrieval-augmented generation (RAG), and prompt-based workflows. Demonstrate commitment to continuous learning and professional development in AI and data science technologies. Share knowledge with team members, business stakeholders, and IT partners.

Requirements

Bachelor's degree in computer science, Data Science, Information Systems, Mathematics, Statistics, Engineering, or related fields
Relevant experience in data science, analytics, software development, or other quantitative disciplines. Internship, research, academic, or project-based experience applying analytical and machine learning techniques may be considered
Foundational experience with Python and data analysis libraries such as Pandas, NumPy, Scikit-learn, PySpark, or similar technologies. Ability to develop scripts, perform data analysis, and support analytical solution development
Basic knowledge of machine learning, artificial intelligence, statistics, data visualization, or data mining concepts. Familiarity with Large Language Models (LLMs), prompt engineering, retrieval-augmented generation (RAG), or modern AI technologies
Ability to access, cleanse, transform, and analyze structured and unstructured data from multiple sources. Familiarity with data quality concepts, data preparation techniques, and modern data platforms
Understanding software development fundamentals, version control practices, and collaborative development methodologies
Awareness of Responsible AI principles, data privacy requirements, and the importance of working with sensitive, regulated, or export-controlled data in a secure and compliant manner
Strong analytical, problem-solving, and communication skills, with the ability to present findings and recommendations clearly to technical and non-technical audiences

Nice To Haves

Familiarity with Azure AI services, Azure OpenAI, Databricks, and modern cloud-based analytics platforms. Experience with Python and/or SQL, and exposure to analytical tools and languages such as R, SAS, Stata, SPSS, PySpark, or equivalent technologies. Familiarity with querying and working with structured and unstructured datasets
Foundational knowledge of machine learning, statistics, probability, and data analytics concepts. Exposure to AI and GenAI technologies, including large language models (LLMs), prompt engineering, retrieval-augmented generation (RAG), or agent-based AI frameworks through academic, personal, internship, or professional experience
Internship, academic, research, or professional experience within the energy, utilities, manufacturing, or other data-intensive industries
Exposure to operational, engineering, or equipment performance data

Responsibilities

Support the development and implementation of data science, machine learning, and AI solutions that help improve business performance, operational effectiveness, and decision-making across nuclear and enterprise business functions.
Analyze structured and unstructured data using established statistical, analytical, and machine learning techniques. Apply tools such as Python, SQL, PySpark, Scikit-learn, and similar technologies under the guidance of senior team members.
Assist in the development, testing, and evaluation of AI-enabled solutions, including foundational exposure to large language models (LLMs), prompt engineering, retrieval-augmented generation (RAG), and other emerging AI capabilities.
Access, cleanse, transform, and prepare data from enterprise systems, data warehouses, and data lakes. Support data quality initiatives and work with layered data architectures to enable analytics and AI use cases.
Develop and maintain analytical notebooks, scripts, and supporting documentation following established development standards, testing practices, and version control procedures.
Collaborate with data scientists, engineers, product teams, and business stakeholders to understand requirements and contribute to the delivery of analytical and AI-driven solutions.
Communicate findings, insights, and recommendations through reports, visualizations, presentations, and documentation tailored to technical and non-technical audiences.
Apply established governance, security, and compliance requirements, including PII handling, Export Control (ECI) requirements, and responsible AI practices.
Support model validation, monitoring, and performance measurement activities to help ensure analytical and AI solutions remain accurate, reliable, and effective.
Continuously develop technical, analytical, and business knowledge through training, mentorship, and hands-on experience while contributing to a collaborative and innovation-focused team environment.