Fraud Detection: Developing models to identify unusual patterns or anomalies in transaction data that might indicate fraudulent activities.

Predictive Maintenance: Creating models that predict equipment failures based on sensor data. This can help companies minimize downtime and save on repair costs.

Customer Churn Prediction: Creating models to predict which customers will quit using a product or service based on their usage patterns, feedback, and other behavior, helping businesses improve retention.

Demand Forecasting: Developing models forecasting demand for various products or services, helping companies optimize their supply chains and manage inventory effectively.

Personalized Marketing: Developing models that analyze customer behavior and create personalized marketing strategies or recommendations for marketing and sales, enhancing customer engagement and increasing sales.

Automated Resume Screening: Creating machine learning models that automatically screen resumes and shortlist candidates, speeding up the hiring process.

Health Diagnosis: Designing machine learning algorithms that predict disease progression or assist in diagnosis based on patient data.

Real Estate Pricing: Creating models that predict property prices based on location, size, amenities, etc., helping businesses and individuals make informed decisions.