Assoc Analyst, IT AI

Tractor Supply Company•Brentwood, TN

23h•Hybrid

About The Position

This position supports the development, testing, and maintenance of artificial intelligence and machine learning solutions that enable data-driven decision-making and operational efficiency across the organization.

Requirements

2+ years of experience in software engineering, data science, analytics, or machine learning. Experience gained through internships, academic projects, or entry-level roles.
Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field preferred. Any suitable combination of education and experience will be considered.
Entry-level AI, ML, or cloud certifications preferred.

Nice To Haves

Foundational knowledge of machine learning concepts and data structures.
Proficiency in Python or similar programming languages.
Strong analytical, problem-solving, and troubleshooting skills.
Ability to work effectively in a team-oriented environment.

Responsibilities

Assist in the development, testing, validation, and deployment of AI and machine learning models and applications to support business use cases.
Support data collection, preparation, feature engineering, and model training activities, ensuring data quality, reproducibility, and adherence to established standards and best practices.
Perform maintenance, monitoring, and minor enhancements to existing AI solutions to improve reliability, performance, and accuracy over time.
Analyze datasets to identify patterns, trends, and insights that inform model development and business decision-making.
Collaborate with engineers, analysts, product teams, and business partners to understand requirements, translate business needs into technical specifications, and support solution design.
Assist with model evaluation and validation, including performance measurement, error analysis, and identification of potential bias or risk.
Create documentation, reports, and basic visualizations to communicate findings, model behavior, and outcomes to technical and non-technical stakeholders.
Adhere to established development, security, data governance, and responsible AI standards, including ethical use, privacy, and compliance requirements.
Stay current with emerging AI and machine learning tools, techniques, and best practices, and identify opportunities for continuous improvement.