Hi, I’m Jayant Dabas.
A Machine Learning Engineer and Graduate Student in Data Science at NYU.
A Machine Learning Engineer and Graduate Student in Data Science at NYU.
Looking for my next
opportunity
to make a change.
The digital way.
opportunity
to make a change.
The digital way.
Hi, I’m Jayant Dabas.
A Machine Learning Engineer and Graduate Student in Data Science at NYU.
A Machine Learning Engineer and Graduate Student in Data Science at NYU.
Hi, I’m Jayant Dabas.
A Machine Learning Engineer and Graduate Student in Data Science at NYU.
A Machine Learning Engineer and Graduate Student in Data Science at NYU.
Looking for my next
opportunity
to make a change.
The digital way.
opportunity
to make a change.
The digital way.
Looking for my next
opportunity
to make a change.
The digital way.
opportunity
to make a change.
The digital way.
This is me
Intro
Hi, I'm Jayant Dabas, a Machine Learning Engineer, and the founder of AnalyticsQ. I'm currently pursuing a graduate degree in Data Science at New York University, where I focus on understanding how modern AI systems reason, adapt, and make decisions, and how they can be improved to be more reliable, interpretable, and impactful.
In my previous roles, I've worked as a Software Engineer, DevOps Engineer, and Data Analyst while collaborating with diverse teams in APAC and North America to design, build, and deploy scalable and reliable applications.
Life Story
My interest in technology started with a genuine curiosity. In middle school, after reading a computer science book that described how machines could “think,” I became fascinated by the idea of building systems that could learn, automate and evolve from experience. That excitement shaped everything that followed.
Since then, my path has moved between software engineering and machine learning, from building full-stack and backend systems to developing and evaluating models. What keeps me motivated is solving problems that are both technically challenging and genuinely useful to people.
Free Time
When I'm away from work, I like to stay grounded in the physical world. I spend time hiking, running, playing soccer, bouldering, and training at the gym. I also enjoy painting, cooking, listening to music, and being around animals and nature.
My Experience
Herndon, VA
May 2025 ー Aug 2025
Machine Learning Engineer Intern
- Built an AI Agent for global AWS metering analysis that cut investigation time by 87%, safeguarding $11M+ daily revenue.
- Designed a Gen-AI agent to automate manual workflows and doubled monthly usage metering investigations, processing over 614B records/min.
- Deployed an end-to-end ML model with Amazon Q, MCP, and AWS (S3, EC2, DynamoDB) to detect data transfer inconsistencies that lowered engineering costs by 20% and tripled throughput.
- Contributed to Amazon Q CLI by enhancing MCP client to enhance agentic flows and multi-step decision making.
New York, NY
Mar 2025 ー Present
Graduate Research Assistant - Causal Inference in LLMs
- Reproduced and extended Rehder & Hastie's "Categorization as Causal Reasoning" experiments using LLMs as cognitive models, implementing generative pipelines that simulate human-like category judgments under varying causal structures.
- Built and deployed statistical inference modules using regression to analyze model outputs across 288 adaptive scenarios.
- Designed an end-to-end evaluation pipeline for data simulation, model inference, and result visualization, ensuring reproducibility and scalable extension to new domains.
- Applied causal inference techniques to quantify human-model divergences, using metrics to assess how structural priors influence generalization behavior.
Nov 2024 ー Present
Graduate Research Assistant - Data Science
- Developed predictive models using Python and regression analysis to quantify the impact of economic development, resource access, and electoral competitiveness on gender disparities in voter turnout.
- Engineered a data pipeline to process and merge large-scale voter datasets, reducing preprocessing time by 40%.
- Visualized trends in gender-based voting behavior using Matplotlib and Seaborn, improving stakeholder insights.
Tokyo, Japan
Oct 2022 ー Jul 2024
Data Scientist, AI Engineer
- Built an ML pipeline using Microsoft Azure, OpenAI API, and BigQuery to enrich 200K+ product listings on Rakuma, achieving 92% attribute extraction accuracy across 5 retail categories.
- Designed and deployed an NLP relevance scoring model leveraging semantic embeddings and cosine similarity, boosting review engagement by 18% through improved personalization.
- Automated 30+ backend workflows using Apache Airflow DAGs and REST integrations, cutting manual operations by 75% and accelerating model retraining and data ingestion cycles.
- Collaborated with cross-functional teams to deploy model APIs into production using Docker and Kubernetes, ensuring low-latency inference for real-time enrichment.
New Delhi, India
Aug 2020 ー Jun 2024
Founder and Director of Technology
- Led a diverse team of 5+ professionals to design and develop AnalyticsQ, an enterprise-level data analytics tool that optimizes data processing, saving time and resources by 60%.
- Secured $100,000 in seed funding to scale the product, expanding its adoption to 100+ customers.
- Directed project timelines, developed features, and managed business team to ensure successful delivery.
- Built predictive features, enabling businesses to identify revenue opportunities with 20% higher precision.
Kowloon, Hong Kong
Sept 2020 ー May 2021
DevOps Engineering Intern
- Automated application pipelines for IBM Urban Cloud to allow 32% quicker and more efficient releases.
- Discovered and enhanced cloud security frameworks to address privacy issues and ensure data integrity.
- Analyzed performance metrics to identify bottlenecks, optimizing system performance by 15%.
Kowloon, Hong Kong
Sept 2019 ー Apr 2021
Research Assistant - Active Learning
- Supported data collection and prepared experiments for Dr. Xueying Zhan's research on active learning models, contributing to the paper "A Comparative Survey of Deep Active Learning" (Zhan et al., 2022).
- Conducted data analysis to assist in the evaluation of models, identifying patterns to support research findings.
Apr 2019 ー Apr 2020
IoT and Mobile App Developer
- Designed and developed the official CityU mobile app in Flutter with 120K+ downloads to enable student access.
- Implemented APIs with MuleSoft, tested with Postman, and used JIRA for Agile development.
Apr 2019 ー Jun 2019
Data Analyst
- Developed an end-to-end ETL pipeline to extract, transform, and analyze 50 years of geopolitical and social event data from Google's GDELT dataset.
- Implemented parallel processing in Apache Spark, reducing data processing time by 36 hours.
Projects I've Built
Open Source Retrieval-Augmented Generation (RAG) pipeline for managing project information and facilitating team collaboration
- Built a modular RAG pipeline using FastAPI and Mistral AI to deliver citation-backed insights from documents and meetings.
- Designed a hybrid retrieval engine and local vector store with hallucination filtering, policy-based query refusal, and adaptive prompt generation, achieving high reliability and zero dependency on external databases.
Natural Language Understanding - New York University, New York, NY
- Evaluated state-of-the-art LLMs on their ability to process and retain complex causal relationships over time.
- Introduced a Real-Time Adaptation Challenge to assess LLMs' reasoning accuracy under dynamic scenarios.
Cryptography - Web applications
- Published an open source lightweight, standalone password hashing library with zero external dependencies.
- Compatible with Node.js, Next.js, and most browsers, providing a simple API similar to bcrypt.js.
- Available for use at https://www.npmjs.com/package/bcrypt-mini
Research thesis - City University of Hong Kong, Hong Kong
- Wrote a research paper on a zero-shot learning method used in unfamiliar object classification in autonomous vehicles, NLP, or detection of unforeseen diseases in medical imaging such as X-rays
- Employed generative approach with text captions to creatively extend the model to new domains
MiraiDensei Ltd - India
- Led a team of motivated and qualified people with various skills to develop AnalyticsQ, an enterprise-level automation tool that uses real-time analysis and interactive pipelines to save time and resources by 60%
- Developed the platform using technologies like React, Node, Express, PostgreSQL, Python, and more
- It received seed funding of HK $100,000 from Hong Kong Science and Technology Park in 2021
Data Intensive Computing - City University of Hong Kong
- Analyzed COVID-19 news articles of the past 2 years to identified its propagation and impact worldwide
- Presented the results by building a visualizer using Apache Spark, Python, and JavaScript to analyze the big data from the GDELT dataset provided by Google
- The Data Extraction using Spark significantly improved resource allocation improving the CPU performance by 36% and the memory performance by 14%
City University of Hong Kong - Hong Kong
- Developed CityU Mobile, which is an official mobile app of City University of Hong Kong
- It is one of the top-rated University apps in Hong Kong, with over 100,000 downloads each term
- Implemented internal authentication APIs with MuleSoft and tested with Postman
Contact
My inbox is always open. Whether you have a question or just want to say hi, I'll try my best to get back to you!
Say Hello!