Junior Data Scientist

Location: Indianapolis

Junior Data Scientist page is loaded## Junior Data Scientist remote type:
On Site locations:
US, Indianapolis, INtime type:
Full time posted on:
Posted Todayjob requisition :
R1061631
** Fortune 500 company
** that's leading the charge in the global energy revolution. With operations spanning
** 14 countries**, AES is committed to shaping a future through innovation and collaboration. Our dedication to innovation has earned us recognition as one of the
** Top Ten Best Workplaces for Innovators
** by Fast Company in 2022. And with our certification as a
** Great Place to Work**, you can be confident that you're joining a company that values its people just as much as its groundbreaking ideas.

AES is proudly
** ranked #1 globally
** in renewable energy sales to corporations, and with **$12.7B in revenues in 2023**, we have the resources and expertise to make a significant impact as we provide electricity to
** 25 million customers worldwide.
** As the world moves towards a net-zero future, AES is committed to meeting the Paris Agreement's goals by 2050. Our innovative solutions, such as
** 24/7 carbon-free energy
** for data centers, are setting the pace for rapid, global decarbonization.

If you're ready to be part of a company that's not just adapting to change, but driving it, AES is the place for you. We're not just building a cleaner, more sustainable future - we're powering it. Apply now and energize your career with a true leader in the global energy transformation.
** Position Summary
** The Junior Data Scientist will support AES’s US Utilities operations by applying data science techniques to improve grid reliability, customer experience, and operational efficiency. This entry-level role is ideal for candidates passionate about solving real-world energy challenges through data exploration, predictive modeling, and cross-functional collaboration. You’ll work alongside our team of experienced data scientists, data analysts, data architects and engineers, and data governance experts to deliver insights that drive smarter decisions and accelerate the future of energy.
** Key Responsibilities
*** Work cross-functionally within the team of data scientists, data architects & engineers, machine learning engineers, data analysts, and data governance experts to support integrated data solutions.
* Collaborate with business stakeholders and business analysts to define project requirements.
* Collect, clean, and preprocess structured and unstructured data from utility systems (e.g., meter data, customer data).
* Perform exploratory data analysis to identify trends, anomalies, and opportunities for improvement in grid operations and customer service.
* Use both traditional machine learning methods and generative AI tools to create predictive models that solve utilities-focused problems, particularly in the customer space (e.g., outage restoration, customer program adoption, revenue assurance).
* Present data-driven insights to internal stakeholders in a clear, concise manner, including visualizing data to provide predictive insights and drive decision making.
* Document methodologies, workflows, and results to ensure reproducibility and transparency.
* Be a champion of data and AI at all levels of the AES US Utilities organization.
* Stay current with industry trends in utility analytics and machine learning.
** Qualifications
* *** Must Have
*** Bachelor’s degree in data science, statistics, computer science, engineering, or a related field.  Master’s degree or Ph.D. is preferred.
* 5 years of experience in a data science or analytics role.
* Strong applied analytics and statistics skills, such as distributions, statistical testing, regression, etc.
* Proficiency in Python or R, with experience using libraries such as pandas, Num Py, and scikit-learn.
* Proficiency in traditional machine learning algorithms and techniques, including k-nearest neighbors (k-NN), naive Bayes, support vector machines (SVM), convolutional neural networks (CNN), random forest, gradient-boosted trees, etc.
* Familiarity with generative AI tools and techniques, including large language models (LLMs) and Retrieval-Augmented Generation (RAG), with an…