Job Description
Location: Atlanta
Duration: Summer 2026 | 3–6 Months
Department: Data Science / Machine Learning
About GAINS GAINS is on a mission to make supply chains smarter, faster, and self-improving, powered by AI. Our decision intelligence platform doesn't just support decisions, it drives them by aligning strategy, planning, and execution across every level of the supply chain. We serve inventory-intensive industries where the stakes are high and the complexity is real, helping customers move from reactive, spreadsheet-driven planning to continuously learning, AI-led operations that deliver measurable results fast. At GAINS, we call it Moving Forward Faster— and it's not a tagline, it's how we're redefining what's possible in driving supply chain decisions.
About the Role We are looking for a motivated and technically curious Data Science Intern to join our team. You will work alongside experienced data scientists and engineers on real-world problems, contributing to feature engineering, data pipeline development, and automation workflows that power our machine learning initiatives. This is a hands-on role where your code ships to production systems.
What You'll Do - Design and implement **feature engineering pipelines** to prepare data for machine learning models
- Build and maintain **automated data pipelines** for ingestion, transformation, and validation
- Develop Python scripts and utilities to streamline repetitive data science workflows
- Collaborate with the data science team to understand business requirements and translate them into clean, testable code
- Use AI coding tools (e.g., GitHub Copilot, Claude, ChatGPT) fluently to accelerate development and improve code quality
- Document your work clearly so that pipelines and features are maintainable and reproducible
What We're Looking For Must Have - Currently enrolled in a Bachelor's or Master's program in Computer Science, Data Science, Statistics, Mathematics, or a related field
- Strong proficiency in **Python** (pandas, NumPy, scikit-learn)
- Foundational understanding of **data science concepts** — supervised/unsupervised learning, model evaluation, feature selection
- Demonstrated ability to use **AI tools to write, debug, and refactor code** effectively
- Comfort working with structured and semi-structured data (CSV, JSON, SQL)
Nice to Have - Familiarity with **Azure** cloud services (Azure Data Lake, Azure Data Factory, or similar)
- Exposure to **Databricks** — notebooks, Delta tables, or Spark-based data processing
- Experience with **MLflow** for experiment tracking and model management
- Experience with version control (Git) and collaborative development workflows
- Basic understanding of data quality and testing practices
What You'll Gain - Hands-on experience building production-grade data pipelines and ML-ready feature sets
- Mentorship from senior data scientists and platform engineers
- Exposure to modern MLOps tooling and cloud-based data infrastructure
- Real impact — your work will directly support model training and deployment workflows
Why GAINS - Work on software that leverages AI and ML to solve real logistics challenges for customers
- Direct impact on developer experience across the entire engineering org
- Collaborative, low-bureaucracy environment where engineers own their work end-to-end
- Competitive compensation and benefits
We are committed to equal employment opportunity and welcome everyone regardless of race, color, ancestry, religion, national origin, age, sex, gender identity, sexual orientation, disability, marital status, domestic partner status, veteran status or medical condition. We encourage people from all backgrounds to apply.
Job Tags
Summer work