Working as a machine learning enginner in the company's central
automation team, responsibilities include finding the scope of
automation in different ongoing projects and then develop the same
using different automation methodologies.
Developed the product called "Infosys Intelligent Assistant" from scratch,
which automates entire L1 & L2 workflow for the IT Service Management
using Machine Learning approaches on ITSM tickets.
Applied different vectorization techniques like BOW, Tf-Idf & Tf-Idf
weighted W2V on the ticket data.
Implemented Logistic Regression, SVC, Random Forest & XGBoost.
Applied Bayesian optimisation for hyperparameter tuning using AUC
metric.
Achieved F1 score of 0.81 from Logistic Regression & Tf-Idf.

Developed a NER model for identifying names of servers, persons,
applications etc. from the ticket description using Kaggle NER dataset as
well as client custom annotated dataset and a pre-trained BERT model.
Working on Image & Time-Series based tasks to identify the error logs
and predict failure scenarios before happening

Worked on News Data on Kaggle to classify news based on the headline using Different Text Classification techniques.

Worked on Kaggle problem of Survival Prediction on Titanic secured 3000 rank, worked & explored numeric-continuous & categorical data.