GAINSystems→
Data Science Intern at GAINSystems in Atlanta, GA
InternshipOn-siteFull-timeAtlanta, GA
Skills
pythonpandasnumpyscikit-learnazuredatabricksmlflowgit
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
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