Machine Learning Intern

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About the Role

This internship focuses on applying machine learning and analytical methods to real business data in the financial distribution domain. The role involves model development, research, insight generation, and supporting strategic decision-making.

Key Responsibilities

• Research and identify AI/ML applications relevant to Mutual Funds, SIPs, and Insurance workflows.
• Analyze customer behavior, sales trends, and performance metrics to derive actionable insights.
• Develop basic predictive and recommendation models such as churn prediction, segmentation, and investment pattern analysis.
• Identify areas for workflow automation, including lead qualification and client servicing.
• Work with business and product teams to convert analytical insights into measurable solutions.
• Present findings through structured reports, dashboards, or presentations.
• Benchmark market and competitor practices in AI-driven financial advisory tools.

Requirements

• Strong foundation in Machine Learning, Data Analytics, and Python programming.
• Experience with ML libraries such as pandas, NumPy, scikit-learn, TensorFlow, or PyTorch.
• Familiarity with financial instruments (SIPs, Mutual Funds, Insurance) is preferred but not mandatory.
• Ability to create visualizations using Power BI, Tableau, or Python visualization libraries.
• Strong analytical reasoning, communication skills, and ability to work independently.

Suitable For

• Candidates interested in roles such as Machine Learning Engineer Intern, Data Science Intern, AI Research Intern, or Quantitative Analyst Intern.
• Students looking to apply ML techniques to real-world business and financial datasets.