Advanced Data Scientist - GenAI, Experimentation, & Computer Vision

American Electric Power•Columbus, OH

About The Position

At American Electric Power (AEP), we are building a modern AI and analytics ecosystem to empower teams across the company to use AI responsibly and effectively. We are seeking an Advanced Data Scientist who combines strong statistical foundations with hands-on software engineering skills to take ideas from research through experimentation, validation, and deployment. This role involves being a technical leader in applying a variety of GenAI techniques to real business problems, alongside traditional AI/ML, with a specific focus on computer vision for drone imagery. The position will contribute to shaping the team's tooling and development patterns, partnering with business units to understand AI/ML needs, and mentoring other data scientists to enhance AI delivery across the company.

Requirements

Bachelor's degree in mathematics, operations research, statistics, economics, data science, computer science or related technical field is required.
8 years of experience required.
An equivalent combination of education and related experience may be considered.

Nice To Haves

Experience delivering end-to-end AI/ML solutions from experimentation through production.
Strong foundation in statistics and experimental design, including model evaluation and success metrics.
Hands-on experience building models across traditional ML and GenAI, with sound judgment on approach selection.
Experience applying computer vision techniques and building scalable imagery-based ML pipelines.
Solid software engineering practices, including reproducibility, version control, and reusable code.
Practical MLOps experience with model packaging, deployment, tracking, and monitoring.
Ability to translate business needs into technical direction and clearly communicate tradeoffs.
Demonstrated technical leadership through mentoring, review, and influence.
Strong Python skills for ML development; working knowledge of R preferred.

Responsibilities

Design, build, and deploy AI/ML solutions using a mix of traditional ML and GenAI techniques.
Apply strong statistical judgment to model selection, evaluation, and validation.
Incorporate computer vision techniques where appropriate, including imagery-based use cases such as drone data.
Design and run experiments to evaluate model performance and business impact.
Define success metrics, validation approaches, and acceptance criteria for AI solutions.
Perform error analysis, robustness checks, and performance tuning prior to production use.
Package and deploy models using established pipelines and platforms.
Apply best practices for versioning, reproducibility, and experiment tracking.
Help guide and improve the tools, platforms, and development patterns used by data scientists across teams.
Work with business units to understand AI/ML needs and identify high-value use cases.
Translate business problems into clear technical approaches and delivery plans.
Communicate results, tradeoffs, and recommendations to both technical and non-technical stakeholders.
Provide technical guidance and review for other data scientists and partner teams.
Mentor peers on modeling approaches, experimentation, and production delivery.
Serve as a role model for high-quality, responsible, and scalable AI/ML work across the company.