
Senior Lead Machine Learning Engineer @ CapitalOne
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
- An experienced engineer in the field of Data Science, Machine Learning, and Statistics.
Indiana University Bloomington
Master’s Degree, Data Science
January 1, 2016 – January 1, 2018
Anna University
Engineer's Degree, Computer Sciene and Engineering
January 1, 2011 – January 1, 2015
Capital One
Senior Lead Machine Learning Engineer
May 1, 2026 – Present
Chewy
Lead Machine Learning Scientist
September 1, 2024 – May 1, 2026
The Home Depot
Lead Machine Learning Engineer
March 1, 2023 – September 1, 2024
Wayfair
Senior Machine Learning Scientist
June 1, 2022 – March 1, 2023
Amazon Web Services (AWS)
Software Engineer - Machine learning
October 1, 2019 – May 1, 2022
New York, United States
Nordstrom
Data Science Engineer
July 1, 2018 – October 1, 2019
Greater Seattle Area
Indiana University Bloomington
Associate Instructor
August 1, 2016 – May 1, 2018
Bloomington, Indiana
Zoho Corporation
Software Engineeer
December 1, 2014 – July 1, 2016
Knowledge Graph Representation on an Ontology
August 1, 2017 – November 1, 2017
Python, Neo4J - Cypher, AWS – EC2, Spacy, StanfordCoreNLP, OpenNLP, Kafka • Contributed to a pipeline in which natural text of about 1TB from Wikipedia is parsed, saved in a graph (Neo4J) and can be queried upon. • One of the two AWS instance parses the data and extracts the NLP information using Spacy, Stanford Core NLP & Open NLP which is stored in Neo4J in the other instance. • Contributed in storing the data in Neo4J by defining the Ontology using OWL, writing dynamic Cypher queries and then querying the data.
Zappos – Search Functionality – Android
April 1, 2017 – May 1, 2017
• Collaborated with the Android team at Zappos to work on the Search functionality and product display page of the Zappos Android app. • Collaborated with the API team and used retrofit to fetch data from the server. Enabled offline mode by caching data. • Enabled product sharing using a magic link and worked on animations ensure great user experience thereby following the material design guidelines.
Speech Separation, Identification and Automatic Speech Recognition
February 1, 2017 – Present
• Implemented Deep feed forward Neural Network and Long Short-term memory neural network to separate speech from background noise using Complex ratio masks improving the accuracy of the algorithms to 3.073 PESQ with a training set of about 14,400 generated noisy speech and a test set of 1400 samples. • Performed Automatic Speech Recognition using Hidden Markov Model Toolkit and Kaldi on the denoised data.
Sarcasm Detection
February 1, 2017 – April 1, 2017
• Collected twitter data with the hashtag #sarcasm and manually validated the tweets to be used as my training data set. • Developed n-gram model, performed sentiment analysis, generated parts of speech tags & collected the bag of words from the dataset. • The overall accuracy of the model is 0.65 (F-score) in which N-gram performed better when tested individually (0.61) followed by sentiment analysis (0.46).
Approval Ratings – US President, Canadian Prime Minister
January 1, 2017 – May 1, 2017
• Collected a total 1.5 million tweets for both the leaders containing certain keywords and pre-processed the data on an AWS instance (Amazon Web Services Server). • Performed Sentiment Analysis using Affin, SentiwordNet and custom lexicon check on the 400,000 tweets collected every month for almost four months. • Used Cross Validation to calculate the accuracy (90%).The results are more detailed and accurate than the famous Gallop poll.
Artificial Intelligence Projects
November 1, 2016 – December 1, 2016
• Implemented a Map search algorithm for a USA dataset using BFS, DFS, IDS and A-star algorithm to find the optimal, shortest, longest and fastest path between places. • Implemented n-k-coh-coh (variant of X-O) game using alpha beta pruning and minimax algorithm. • Implemented machine learning algorithms such as Naïve Bayes and Decision trees for Spam/Non-Spam mail filtering.
Fast Learn
May 1, 2016 – Present
• As a side project, collaborated with my team and the computer science department of my university to design and implement a student-teacher community portal. • Contributed to the controller part of the application by designing and coding the servlets enabling proper logic flow within the application.
Eliminating Redundancy in File System Using Data Compression and Secured File Sharing
April 1, 2015 – Present
There are many files of same type-size-quality and content being shared across social media in the recent times. To ensure that the redundancy is prevented we designed a storing and sharing software wherein we implemented this redundancy check by comparing files and ensuring redundancy is avoided. Similar use case can also be used in messaging applications or e-mailing applications. When the same image is being forwarded by multiple people and when downloaded these applications don’t make sure redundancy is prevented. Hence, we went ahead and implemented this solution.
Multiclip
October 1, 2014 – Present
In present day mobile phones, the users can copy and paste only one item at a time. Since, app switching in mobile phones is quite costly in terms of processing and the number of times app switching is needed to copy multiple stuff from one app to another from multiple sources is quite a lot of times. We solved this issue by helping user copy multiple stuff at a time and paste all of them at a time between applications by using content provider. Also, to ensure sensitive data has not been copied and persisted control check has been programmed.
Mutual Data protection in cloud computing Environment
January 1, 2013 – Present
To ensure and enhance the security of the customer’s data in a third party cloud provider we proposed four techniques over time such as Colouring Technique, Login-out code, Messaging Code, Binary Code conversion Technique.
Cultural Fit Analysis
The candidate's career trajectory shows a strong focus on Machine Learning and Data Science, with significant roles in large enterprises. While there is a foundational background in Android development from earlier roles and a specific project (Zappos), the recent experience is heavily skewed towards ML. This might indicate a potential mismatch for a pure Android Developer role, as the candidate's primary career path has diverged. The diversity of projects, however, shows adaptability and a broad technical interest.
Soft Skills & Operational Fit
The candidate's experience as an Associate Instructor and in lead roles suggests strong communication and leadership skills. Project descriptions indicate a problem-solving mindset and collaboration experience. However, without specific psychometric test results, a detailed assessment of work attitude, stress handling, and team collaboration is not possible.