Nov 2022 – Dec 2025 · 3 yrs 1 mo · Cupertino, California, United States

Jun 2021 – Nov 2022 · 1 yr 5 mos · San Francisco Bay Area

Nov 2020 – Jun 2021 · 7 mos

Jan 2019 – Oct 2020 · 1 yr 9 mos

Sep 2018 – Dec 2018 · 3 mos · New York City Metropolitan Area

• Built a C library for l1 trend filtering technique.
• Worked on trend filtering for time series data using l1 regularization as a function of time.

Jan 2018 – May 2018 · 4 mos · New York City Metropolitan Area

• Teaching Assistant under Prof. Xiaofu He for graduate level course "Applied Machine learning for Image Analysis"
• Grade assignments for a class of 44 students

Aug 2017 – Dec 2017 · 4 mos · New York City Metropolitan Area

• Teaching Assistant under Prof. Adam Kelleher (Cheif Data Scientist for Research at Barclays) for graduate level course "Machine learning products for Data Science"
• Graded assignments for a class of 34
• Conducted weekly office hours to assist students in udnerstanding the course material

May 2018 – Aug 2018 · 3 mos · Greater Pittsburgh Region

• Built a topic segmentation model for detecting the topic change in speech transcripts.
• Implemented a sequence classification model using Fasttext word embeddings.
• Developed a model for topic summarization from transcripts.

Mar 2016 – Jul 2017 · 1 yr 4 mos · Greater Chennai Area

• Did research on Decision Support Systems using data from aviation industry
• Applied advanced statistical and data science skills to conduct exploration and research on the data

Jun 2015 – Nov 2015 · 5 mos · Mumbai Metropolitan Region

• Ad Relevance Engine [PostgreSQL, Python, Django]
• Developed a relevance engine in Django for real estate advertisements using elastic search server
• The engine uses user intents (from preference modeling) and a modified collaborative filtering technique which we named as "Intent Matrix Factorization"; Website conversion rate was raised by 30% and bounce rate was reduced by 40%
• Similar Entities on Housing website [MongoDB, Python, Django]
• Built Web App in Django to serve similar flats using Mongo database; Application uses K-means to cluster similar flats
• Intra cluster similarity score is calculated from normalized Euclidean distance between the flat features
• Increased the popularity of the website thus increasing property listings by dealers
• Monitoring Relevance of Search Results [R, Shiny, Elastic Search]
• Developed a dashboard in R to analyze the efficacy of the search relevance algorithm and to visualize user engagement
• Devised sampling strategies to match demand and supply; Proposed use of Bandit algorithms for algorithm testing
• Enabled property developers to offer best bids for a given search rank resulting in increased profits (~10 million INR)
• Auto-suggest while typing (like google search) [MongoDB, Python, Django]
• Built an app in Django to aggregate past user search behavior and compute relevance score to sort search suggestions
• Integrated product promotions with search result sorting which increased marketing revenues of the company

Jun 2014 – Jul 2014 · 1 mo · Greater Bengaluru Area

• Manufacturing Data Analytics
• Developed a statistical model in R which analyzes the influence of input features of the Fiber Reinforced Plastic molding process on the output (strength and stiffness) using Design Of Experiments modeling techniques
• Data mapping
• Mapped huge amount of data between two dissimilar meshes ​ 10 million data points
• Developed a code in Matlab to map and for tensor transformation which saved around INR 5 lakh​ for​ the company from buying mapping tools