About Me
I'm a developer with three years of industry experience in building Machine Learning models. I have a solid background in end-to-end development, with a focus on building generalizable, scalable and efficient solutions.
I take pride in my ability to innovate and think out of the box. I am an expert user of Python and I am familiar with a wide range of tools and frameworks to solve any problem at hand. For me, tools are mediums to put creative throughts into actions. I am a strong advocate of open source and I feel that sharing knowledge is the best way to contribute to the community.
Do you want to know a little more about my hobbies? Have a look at my knowledge graph ↓
My Journey
M.S. Computer Science
@ Arizona State UniversityCloud Computing •
Data Mining •
AI in Robotics •
Data systems for ML •
Knowledge Representation •
- Top 5% in 6/6 courses taken
- 4.0 GPA
- Engineering Graduate Scholarship (rewarded to top 10% candidates).
- Working at Kerner Lab in Partnership with NASA: Ran 10 k+ computer-vision experiments on Mars data using ASU HPC clusters (Slurm + Python).
- Working at Decision Theater @ ASU on real world analytical challenges with partner organizations
Machine Learning Engineer
@ O9 Solutions- Productionised hybrid clustering to optimise inventory for 10 Fortune 500 clients, cutting E2E runtime by 20%.
- Delivered ARIMA-based line-speed forecasts for AB InBev, raising accuracy by 10% & plant throughput 5%.
Machine Learning Engineer
@ Head Digital Works- Won "Innovator of the Year" for card-arrangement optimisation; boosted engagement by 30%, cut fraud by 8%.
- Fast-tracked to MLE in 15 months; shipped 3 revenue-bearing features in year 1.
- Built MLService (AWS event-driven model deployment service), enabling ML-driven marketing campaigns, lifting daily active users by 10% and revenue by 0.25%.
Associate Data Scientist
@ Head Digital Works- Deployed a real-time retention model combining XGBoost & fuzzy logic, raising daily transactions 5%.
- Reshaped A23's loyalty program, segmenting 5.8M+ users through Python and advanced pivot table analytics to compute Lifetime Value (LTV) and balance cost-benefit allocation, enhancing customer retention by 15%
B.E. Electronics & Communication
@ BITS PilaniProjects
Showcasing some of my favorite work and personal projects.
Earnings Call RAG
Finance RAG Bot is a Retrieval-Augmented Generation system designed for analyzing and querying financial documents (Currently supports earnings call transcripts)
Prompt Engineering
Best‑practice prompts and tutorials for large language models.
Machine Learning from Scratch
From-Scratch implementations of classic machine‑learning and deep learning algorithms.
Auto Storage Categorization
NLP‑powered bot that auto‑sorts Google Drive files into logical folders.
Movie Recommendation System
Hybrid recommender merging content clues, ratings, and composite ranking.
Predictive Modelling for Composites
Regression models to optimize composite manufacturing parameters.
Recent Updates
A chronological log of my professional journey and accomplishments.
- Submitted my first paper at NeurIPS under the Dataset & Benchmarks track as a third author (May 2025)
- Completed the Spring 2025 semester with a GPA of 4.22, achieving top 5%ile in Data Intensive Systems for ML and Knowledge Representation (May 2025)
- Started working at Decision Theater @ ASU (April 2025)
- Started volunteering at the Kerner Lab @ ASU (March 2025)
Let's Connect!
Feel free to reach out for collaborations, opportunities, or just to say hello. I'm always open to connecting with fellow data enthusiasts and developers!
Alternatively, drop me an email at ihmehta@asu.edu