Data AI/ML Intern

Data, AI/ML & Advanced Analytics Intern

Overview:
The Data, AI/ML & Advanced Analytics Intern will support both the Enterprise Data & Analytics team and the Data Science & AI Taskforce in building a strong data foundation and prototyping AI‑driven solutions, including machine learning, advanced analytics, and Generative AI experiments, for high‑impact business initiatives. This role provides exposure to modern data platforms, predictive modeling, reporting, and experimentation across the insurance industry, including risk prediction, fraud detection, pricing, claims optimization, and decision support.

Responsibilities:

• Assist in data integration, cleaning, transformation, and feature engineering using SQL, Python, or ETL tools.
• Work with large and varied datasets (telematics, loss history, FMCSA, geospatial, 3rd‑party sources).
• Conduct exploratory data analysis to identify patterns, anomalies, and actionable insights.
• Contribute to exploratory experiments using traditional ML techniques and emerging AI capabilities, documenting findings and recommendations. 
• Support prototyping and experimentation for AI/ML and Generative AI use cases aligned to business needs (e.g., decision support, document intelligence, workflow augmentation). 
• Assist with rapid proof‑of‑concept development, testing hypotheses, evaluating results, and iterating on models and approaches. 
• Support the development and validation of dashboards and reports (Power BI, Cognos, Tableau).
• Participate in data governance activities such as lineage documentation, cataloging, and data quality checks.
• Document workflows, data dictionaries, procedures, experiments, and methodologies.
• Assist in the development, training, and evaluation of models including classification, regression, NLP, computer vision, forecasting, and anomaly detection.
• Contribute to advanced analytics initiatives such as optimization models, risk scoring, and customer segmentation.
• Engage in AI/ML governance discussions, including ethics, fairness, and model monitoring.

Requirements:

• Current enrollment in Computer Science, Data Science, Information Systems, or related program.
• Interest in enterprise data management and modern cloud platforms (Azure, Snowflake, Microsoft Fabric). 
• Familiarity with SQL, Python, and ML/analytics libraries (pandas, scikit-learn, TensorFlow, Pytorch) is a plus.
• Strong analytical and problem solving skills with curiosity to learn new tools, algorithms, and frameworks.
• Prior experience through coursework, research, Kaggle, or internships in data, AI/ML, or analytics is a plus.