Animesh Pandey
Wakefield, Massachusetts, United States
Summary
👤
Senior🎓
Top SchoolAnimesh Pandey is a Senior Software Development Engineer at Amazon with 11 years of experience, currently driving People Engine initiatives and Alexa-related AI tooling. He specializes in backend systems, search, NLP pipelines, and scalable data processing, with hands-on work across Elasticsearch/OpenSearch, Lucene, Java, and Scala. He led a six-month effort to take an internal LLM Evaluation Framework for Conversational Alexa devices from PoC to GA. An active open-source contributor to elastic4s, he expanded the test suite—covering StopTokenFilterPath, analyzers, tokenizers, and filters—and implemented related token-filter features. His career spans Audible/Alexa cross-domain orchestration for Books, Kindle, and Shopping, as well as research roles at Northeastern and Harvard IQSS, and he is based in Wakefield, MA, holding an MS in CS from Northeastern.
11 years of coding experience
9 years of employment as a software developer
High School, High School at Air Force Golden Jubilee InstituteMaster of Science (M.S.), Computer Science, Master of Science (M.S.), Computer Science at Northeastern UniversityBachelor of Technology (B.Tech.), Information Technology, Bachelor of Technology (B.Tech.), Information Technology at Jaypee Institute of Information Technology
Hindi, English
Stackoverflow
5,958reputation
1.6mreached
30answers
205questions
cron
top-5%
Github Skills (21)
elasticsearch710
testing10
elasticsearch810
amazon-elasticsearch10
elasticsearchapi10
scala210
scala10
elasticsearchquery10
aws-elasticsearch10
elasticsearch510
elasticsearch10
elasticsearch610
elasticsearch210
cron9
crontask6
Programming languages (8)
Github contributions (5)
Philippus/elastic4s
Jun 2015 - Jun 2015
🔍 Elasticsearch Scala Client - Reactive, Non Blocking, Type Safe, HTTP Client
Role in this project:
Back-end Developer
Back-end DeveloperContributions:5 commits, 4 PRs, 17 comments in 4 days
Contributions summary:Animesh primarily contributed to the test suite of the `elastic4s` project. Their work centered on adding and modifying tests related to the `StopTokenFilterPath`, demonstrating an understanding of Elasticsearch's text analysis capabilities. They introduced tests for various analyzers, tokenizers, and filters, confirming the correct handling of stop words and other text processing functionalities within the Elasticsearch client library. Additional contributions involved the ApostropheTokenFilter.
non-blockingcircehttp-clientreactive-streamstype-safe
apanimesh061/VaderSentimentJava
Apr 2016 - Nov 2021
Java port of Python NLTK Vader Sentiment Analyzer. VADER (Valence Aware Dictionary and sEntiment Reasoner) is a lexicon and rule-based sentiment analysis tool that is specifically attuned to sentiments expressed in social media, and works well on texts from other domains.
Contributions:2 releases, 1 review, 20 commits in 5 years 8 months
pythonrulejava-8valencesentiment-analyzer
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