Rutvi Macwan Email & Phone Number

Melbourne, Victoria, Australia

• Personalised Modelling: Currently developing a Personalised Recommendation Model to allocate tailored offers to customers, closely collaborating with the commercial teams.
• Predictive Modelling: Achieved generosity savings of $18M through the implementation of Predictive Machine Learning Modelling (Random Forest) by identifying risky customer behaviour on average 3 months before the.
• Data Preprocessing & Feature Engineering: Improved model accuracy from initial 59% to 88% by employing advanced data preprocessing methodologies, including one-hot encoding, label-encoding, strategic class imbalance.
• Data Analysis: Boosted utilisation rate of a recommendation model from 6% to 15% by proactively identifying improvement opportunities through data analysis using pySpark and SQL.
• Cross Functional Team Collaboration: Collaborating with diverse business stakeholders including Data Engineers, MLOps, RPA, and other commercial stakeholders to streamline end-to-end model delivery.
• Data Migration & Leadership: Led a team of 20 people for the successful data and model migration to a new DataBricks platform under tight deadlines.

Melbourne, Victoria, Australia

• Overview: ​​Developed advanced AI functionalities within a product, leveraging cutting-edge technologies including Text Summarization, Amazon Textract and OCR to enhance the product features. Performed feature testing.
• AutoML: Developed various Automated Machine Learning Modelling technologies using AutoML, AutoARIMA and automated clustering algorithms to add functionalities in a product.

Victoria, Australia

• Conducted in-depth analysis and exploration using Python on 8M rows of data gathered from IoT sensors. Achieved an accuracy of 90% by developing an unsupervised AutoEncoder model for anomaly detection in cars.

Bangalore

Bangalore

Mysore, Karnataka, India

Master Of Science - Ms, Data Science, 3.7

Bachelor Of Engineering (B.E.), Computer Engg., 8.55