- Developed a real-time anomaly detection engine to identify abnormal sensor behavior, aiming to reduce waste and enhance maintainability in manufacturing- Developed 40+ unsupervised ways to identify Trends, Outliers, Bunching, Shift, Tolerance, and Seasonal anomalies in families- Implemented a feedback system for users to interact with the model and change the configuration according to need.- Implementing to identify Anomalies in Process Curve data in the manufacturing domain- Anomaly detection helps to save 30% of the cost

- Built Trade Promo Optimization solutions for CPG Customers for different markets and retailers - Used machine learning techniques to predict sales for top-selling products on promotion- Achieved error rate of less than 10% across top-selling products.

- With an aim to bridge the gap between the college curriculum and industry requirements in the field of data science, joined as Co-founder and Head of Data Science- Hosted 5+ offline data science boot camps and assisted them in getting placed in good company- Designed industry-focused curriculum and content with the help of Mentors- Part of the Founder meeting and key members to make a decision for the betterment of the company- As a data and number enthusiast, Analyze candidates/students maps with progress and give insights to the operations team for the smooth conduction of classes

- Built data-driven career coach Careerletics using machine learning and NLP technique- Built LinkedIn pdf parser with 90% accuracy and resume pdf and docs parser with 60 % accuracy.- Worked with partner Mobilieum for Outlier Detection in MAP and Diameter Protocol using Machine Learning and Statistics technique

- Adept at using Stellar trading software for high-frequency trading and traded commodity US Coffee C.- Analysing various fundamental and technical factors that impact the Coffee markets and develop trading strategies accordingly.

OPTIMIZATION OF VENDOR SELECTION PROBLEM USING LINEAR INSTUITIONISTICS FUZZY MODEL.