A Professional with versatile skills and proficiency in android, data science methodologies and machine learning algorithms. Strong planner and problem solver who readily adapts to change, works independently and exceeds expectations. Able to juggle multiple priorities and meet tight deadlines without compromising quality.
o Provided insights to the stakeholders about the performance of the application by analyzing the number of likes, dislikes and shares to meet the customer expectations.
o Maximized the customer engagement from 35% to 40% in mobile application by analyzing the 360-degree view of user experience.
o Improvised the customer experience by hyper-personalization of the web applications based on demographics, past activities and interactions with specific brands.
o Worked with development of credit risk models to help the organisation to decide whether or not to give loans for the borrowers.
o Optimized the contents used in the websites to make it more compelling and engaging by analyzing the click-through rates.
o Performed sentiment analysis on the stakeholders applications by analyzing the socially sourced data like Twitter.
o Experience in migrating the standalone applications to container stack using Docker.
o Built a data warehouse to provide business intelligence by extracting data from various sources (Twitter, Kaggle, Statista) about trends and impacts of machine learning and data science across the nations by deploying an OLAP cube using SSAS to visualize the results in Tableau.
o Built a Hadoop framework for testing the performance of different database like MongoDB, HBase.
o Performed Market Basket Analysis using Apriori Algorithm for effective cross-selling.
o Created an infographic to visualize the insights about a non-profit organization specialized in project funding for school students.
o Built an RNN with LSTM to generate text sequences of the famous authors,so that the works of the renowned authors can be recreated using R programming.
The research project aims to implement the face recognition as the preventive measure against man-in-the-middle attack. A qualitative research technique called transfer learning is used for face recognition along with the liveness detection of eyes to detect whether the person standing before the camera is real, thereby confronting the print attack in face recognition which enhances the security and customer trust in mobile banking.
Apart from being a analytics professional, I enjoy most of my time writing blogs and collecting coins.
Meanwhile, I love to create soulful music when I get free-time, I follow a number of sci-fi and horror genre web-series and I spend a large amount of my free time exploring the latest technology advancements in the analytics world.