Aug 2023 – Mar 2025 · 1 yr 7 mos

• Working on Digital banking Analytics, mainly focussed on Discover Application, a PFM(personal Finance Management)tool in I-Mobile App.

Jul 2022 – Jul 2023 · 1 yr

Aug 2021 – Dec 2021 · 4 mos

• Forecasting PM 2.5 Using Machine Learning models
• Initially previous years data of Kanpur city was collected from CPCB website. This data includes
• Meteorological and air quality parameters.
• Then the data was pre-processed and divided data set into training and testing data set.
• Then fit the XG Boost, Random Forest and Gradient boosting models on training data and trained the model.
• Applied the trained XG Boost, Random Forest and Gradient boosting models on the test data and predicted the pm 2.5 values.
• Finally, calculated the RMSE value of each of the model prediction and decided the best model among the three models.

Apr 2021 – Aug 2021 · 4 mos · Bangalore Urban, Karnataka, India

• Worked on developing AppViewX infrastructure using technologies like Kubernetes, Terraform, Bash scripting, python

Dec 2019 – Jan 2020 · 1 mo · Hyderabad, Telangana, India

• Created a model on Fake News Detection using Machine Learning and achieved accuracy of 92% for our test set.
• Used NLP to process the given news and predicted whether given news is real or fake.
• Initially data was cleaned by removing stop words. Then Tfidf vector was initialized and calculated Tfidf
• scores of words for knowing which words are important in predicting the given news. Later Multinomial
• Naive bayes classifier was used for classifying it as Fake or Real. Finally created user interface for hosting my model on web.