Data Science & Analytics Intern

Overview

This is a unique opportunity to gain broad, hands-on experience across Data Science and Advanced Analytics, while working on high-impact projects with visibility to key business stakeholders. The Data Science & Analytics Intern will support both technical model development and business analytics, translating complex business problems into data-driven insights, models, and compelling narratives. This role is designed for candidates who can operate at the intersection of analytics, data science, and business communication. During recruitment, we are seeking candidates with a strong quantitative foundation who can flex between exploratory analytics, statistical modeling, machine learning, and clear storytelling for business audiences. Interns may be deployed across multiple areas of the analytics and data science team based on project needs.

Reporting Structure: The Data Science & Analytics Intern will report to the Data Analytics Manager within Financial Planning and Analysis Department. Click here to see how you can paint your future!

Responsibilities

• Perform quantitative and exploratory analysis across business and financial domains, including data mining, statistical analysis, and model development
• Translate ambiguous business questions into structured analytical approaches, data pipelines, and model frameworks
• Generate and test hypotheses using appropriate statistical, econometric, or experimental designs and extract actionable insights
• Develop, train, evaluate, and maintain predictive and machine learning models (regression, classification, clustering, time series, etc.)
• Support the design and development of Generative AI solutions and AI agents using Large Language Models (LLMs)
• Assist in building end-to-end data pipelines, from data ingestion and preparation to modeling, validation, and deployment
• Produce analytical reports, dashboards, and visualizations that highlight trends, drivers, and performance against KPIs
• Convert technical findings into clear, business-ready narratives and recommendations for senior leadership
• Partner with business stakeholders to present insights, answer questions, and support decision-making
• Document methodologies, assumptions, results, and recommendations to ensure transparency and reusability
• Identify opportunities for process improvement, automation, and advanced analytics across the organization
• Demonstrate willingness to learn new tools, technologies, and techniques in a rapidly evolving analytics environment

Qualifications

• Currently pursuing a BA/BS or MS in Economics, Statistics, Data Science, Computer Science, Mathematics, or another quantitative discipline
• Strong foundation in statistics, econometrics, experimental design, and analytical problem-solving
• Ability to flex between Data Science (modeling, ML, AI) and Analytics (EDA, reporting, insights) based on business needs
• Proficiency in Python or R, with experience using libraries such as pandas, scikit-learn, TensorFlow, PyTorch, PySpark, or similar
• Experience with data querying and manipulation using SQL
• Familiarity with cloud and data platforms such as Azure ML, Snowflake, or Google Analytics