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Sr. Machine Learning Scientist at Amazon
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
The Ohio State University
Master of Science (M.S.), Computer Science and Engineering, Statistical Data Analysis
January 1, 2013 – January 1, 2015
Vishwakarma Institute Of Technology
Bachelor of Technology (B.Tech.), Computer Engineering
January 1, 2009 – January 1, 2013
Amazon
Senior Machine Learning Scientist
October 1, 2022 – Present
Greater Seattle Area
Amazon
Machine Learning Scientist II
December 1, 2019 – September 1, 2022
Greater Seattle Area
Amazon
Machine Learning Engineer II
October 1, 2017 – November 1, 2019
Greater Seattle Area
Amazon
Machine Learning Engineer
July 1, 2017 – September 1, 2017
Greater Seattle Area
Amazon
Software Development Engineer
October 1, 2016 – June 1, 2017
Greater Seattle Area
Amazon
Software Development Engineer
July 1, 2015 – September 1, 2016
Greater Seattle Area
Department of Computer Science and Engineering, The Ohio State University
Graduate Teaching Associate
January 1, 2015 – May 1, 2015
Columbus, Ohio Area
Department of Biomedical Informatics, The Ohio State University
Intern
May 1, 2014 – October 1, 2014
Columbus, Ohio Area
OLAP over Text Corpora
February 1, 2014 – April 1, 2014
Implemented Online Analytical Processing on a huge unstructured text corpora comprising of ebooks obtained from Project Gutenberg using the premises of full text search, full text indexing, and text mining in MySQL. Designed a similarity metric using the lexicographic tool Wordnet and after preprocessing the text corpora, clustered it using the K-Means algorithm with this similarity metric in PYTHON. Corpora was clustered with different 'k' (number of clusters) values, which was then used as a hierarchy for implementing the ROLL UP and DRILL DOWN operations.
Text Mining on SGML Data
September 1, 2013 – November 1, 2013
Pre-processed, classified, and clustered a huge REUTERS dataset of 21579 documents in PYTHON. Preprocessing: Removed stop words, performed stemming and data selection, and constructed feature vectors. Classification: Predicted document class labels on the preprocessed dataset with KNN Classifier (using Cosine Similarity and Euclidean Distance Metrics), Naive Bayesian Classifier, and Association Rule Mining (using Apriori Algorithm) and measured performance in terms of accuracy, robustness of approach to skew in the training and testing data, scalability, and execution time (online and offline cost). Clustering: Performed clustering using K-Means and DBSCAN algorithms on the preprocessed dataset with Cosine Similarity, Jaccard Similarity, and Manhattan Distance Metrics and analysed clusters obtained w.r.t accuracy, scalability (number of clusters and clustering time), skew, and entropy.
An Efficient Clustering Approach
August 1, 2012 – May 1, 2013
Implemented clustering on an unstructured dataset of images using two algorithms namely DBSCAN and SNN. Evaluated and compared performances of the two algorithms. Implemented in JAVA and awarded the highest grade ‘AA’ for the project.
Three Cards Game
January 1, 2012 – May 1, 2012
Developed a multiplayer card game 'Three Cards' in JAVA as an extracurricular project using SWING framework and multithreading.
e Gas Seva (Service)
August 1, 2011 – November 1, 2011
Designed a fully functional website providing an in-depth service for a cooking-gas cylinder providing agency. UI designed in HTML5 with MySQL as the backend database. PHP used as server side scripting language and for database connectivity.
Cultural Fit Analysis
The candidate has a strong background in research-oriented projects during their academic career, focusing on data analysis and machine learning. Their professional experience at Amazon, progressing from SDE to Senior Machine Learning Scientist, demonstrates a commitment to technical depth and growth within a large, fast-paced organization. While the target role is 'Data Analyst', the candidate's experience leans heavily towards Machine Learning Scientist roles, which might indicate a potential overqualification or a desire for more advanced analytical/modeling work than a typical Data Analyst role. The project diversity shows a breadth of technical interests, but the alignment with a pure 'Data Analyst' role might require further clarification of their career aspirations. The lack of specific company-level cultural fit data makes a deeper assessment challenging.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a strong analytical and problem-solving mindset. Experience as a Graduate Teaching Associate suggests good communication and mentoring skills. The progression through various roles at Amazon (SDE to Senior ML Scientist) indicates adaptability and continuous learning. However, without psychometric test results, a full assessment of work attitude, stress handling, and team collaboration is not possible.