AI & Machine Learning Internship

Responsibilities of the Intern:

• Research and propose AI and ML use cases tailored to the financial distribution domain — especially Mutual Funds, SIPs, and Insurance.
• Analyze customer data, sales patterns, and market trends to derive insights that can increase revenue and client retention.
• Develop basic predictive and recommendation models (e.g., customer segmentation, churn prediction, investment pattern analysis).
• Identify opportunities for automation in sales, lead qualification, and client servicing workflows.
• Collaborate with business and product teams to translate analytical findings into strategy and measurable outcomes.
• Present findings with clarity — via reports, dashboards, or presentations.
• Benchmark competitor and market practices in AI-driven financial advisory.

Requirements:

• Strong foundation in Machine Learning, Data Analytics, and Python programming.
• Familiarity with libraries such as pandas, scikit-learn, NumPy, TensorFlow, or PyTorch.
• Understanding of financial products such as SIPs, Mutual Funds, and Insurance (preferred but not mandatory).
• Proficiency in data visualization (Power BI, Tableau, or Python libraries like Matplotlib/Seaborn).
• Ability to work independently, conduct research, and present findings concisely.
• Strong problem-solving and communication skills.