The AES Corporation is looking to improve grid reliability, customer experience, and operational efficiency in its US Utilities operations by applying data science techniques.
Requirements
- Proficiency in Python or R, with experience using libraries such as pandas, NumPy, 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 understanding of how these can be applied to enhance contextual relevance and integrate enterprise data into intelligent workflows.
- Proficiency in SQL, with experience writing complex queries and working with relational data structures. Google BigQuery experience is preferred, including the use of views, tables, materialized views, stored procedures, etc.
- Proficient in Git for version control, including repository management, branching, merging, and collaborating on code and notebooks in data science projects.
- Proficiency in data visualization tools (e.g., Power BI, Tableau, Looker).
- Experience with cloud computing platforms (GCP preferred)
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.
Other
- Bachelor’s degree in data science, statistics, computer science, engineering, or a related field. Master’s degree or Ph.D. is preferred.
- 7-9 years of experience in a data science or analytics role.
- Ability to manage multiple priorities in a fast-paced environment.
- Interest in learning more about the customer-facing side of the utility industry.
- Valid driver’s license may be required depending on team assignment.
