• Query and manipulate large datasets using tools like SQL, Hive, and Python
• Build and test predictive models using machine learning techniques (e.g., logistic regression, decision trees, clustering)
• Document modeling choices and provides rationale for algorithm selection
• Translate business goals into technical requirements and analytical questions
• Develop a clear and structured final presentation that communicates the project's purpose, methods, insights, and business impact
• Analyze current decisioning models, develop and implement a plan to improve model prediction accuracy
• Improve automation of customer connects via a GenAI enabled chatbot tool
• Use deep learning to uncover hidden trends in fraud and credit bust-out

Programming (Python or R) - Writing scripts for data analysis, modeling, and automation

• Currently enrolled in a full-time Masters degree program
• Master's degree candidates with an expected graduation date between December 2026 and June 2027
• Effective team player with interpersonal skills; capable of working autonomously or collaboratively in cross-functional teams
• Proficiency in the following skills: Programming (Python or R) for data analysis, modeling, and automation; SQL/Hive - Querying large-scale datasets efficiently
• AI Techniques - Experimenting with modern AI methods, including neural networks and natural language processing
• Machine Learning Hands-on experience in machine learning algorithm development or application
• Statistical Analysis - Interpreting data using descriptive and inferential statistics
• Cloud & Big Data Tools - Basic experience with cloud platforms and distributed data systems
• Strategic mindset, that connects work to broader strategy and suggest ideas to enhance scalability and impact
• Prior experience, taking initiative to establish or lead an on-campus student organization
• Proven deep analytical skills with the ability to design new decisioning models or develop innovative tools

Skilled in delivering presentation to wide-ranging audience

Graduate students enrolled in one of the areas below areas or related fields: Computer Science, Statistics, Data Science, Mathematics, Artificial Intelligence

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