A bit about who I am and what I do.
Hey! I'm Najmus — a data analyst and ML practitioner based in Texas. I hold an M.Sc. in Computer Science from Lamar University and a B.Tech. in CSE from NIT Warangal, where I was awarded the ICCR Scholarship by the Government of India.
I've worked across data analytics, machine learning, and software engineering — from analyzing 10M+ clinical records at Script Care Ltd to building developer tools at Amazon Music. My toolkit spans Python, SQL, Scikit-learn, Tensorflow, PyTorch, React, and more. These days I'm diving deeper into AI and exploring what's possible with modern LLMs and generative models.
Outside of work, I'm a passionate Manchester United supporter ☞ yes, even through the rough patches. I unwind by playing video games and getting lost in a good book. I'm currently looking for PhD opportunities in AI/ML and open to exciting full-time roles.
Location
Beaumont, TX, USA
snajmus16@gmail.com
Education
M.Sc. CS, Lamar University
Looking for
PhD & Full-time Roles
My academic journey.
ICCR Scholarship
Full scholarship awarded by the Government of India for talented international students
Inter NIT & IIT ICPC — 2nd Place
Competitive programming competition among India's top technical institutes
Lamar University
Beaumont, TX, USA
Focused on machine learning, distributed systems, and algorithm analysis.
National Institute of Technology Warangal
Warangal, India
Graduated from one of India's premier technical institutes. Recipient of the ICCR Scholarship awarded by the Government of India.
Attentive-Normalized Generation of Images for Semantic Layout Information
Where I've worked and what I've built.
Script Care Ltd
Conducted large-scale statistical research and deployed ML solutions for a leading pharmacy benefits management company.
Lamar University
Applied NLP and machine learning to disaster event detection from social media data.
Amazon Music
Worked on the art19 platform, improving developer tooling and deployment infrastructure for a team of 200+ engineers.
Lamar University
Built data-driven systems and ML models to support university-wide academic decision-making for 8,000+ students and 520+ faculty.
Web and Development Service Centre, NIT Warangal
Developed full-stack MIS applications and data dashboards for a university community of 10,000+ users.
Things I've built — from solo experiments to team collaborations.
Novel GAN architecture for layout-to-image synthesis introducing Attentive Normalization (AN). Trained on MS COCO (70k+ images), achieving FID 38.02 vs. 38.14 baseline and 50.7% vs. 49.8% classification accuracy over Layout2Im. Also applied to CIFAR-10 class imbalance correction.
AI-powered football analytics platform using LangChain and GPT-4o to answer natural-language queries about match data. Analyzes 38-match seasons across MLS and European leagues, generating 10+ derived KPIs. Reduced manual analysis time by ~70%.
End-to-end fraud detection pipeline on the ULB dataset (0.17% fraud rate). Applied SMOTE for class balancing and tuned a Random Forest classifier achieving 98.3% ROC-AUC and 89% recall — identifying the most predictive PCA components (V17, V14, V12).
Python analytics platform processing 20,000+ student records to support data-driven decision-making for 520+ faculty. Features comparative studies, interactive visualizations, and a course recommendation system using Clustering and SVM.
Technologies I work with and love.
A curated reading list that shaped how I think about software.
David Thomas, Andrew Hunt
★★★★★
"Essential reading for any developer. Timeless advice on writing better code and building a career."
Robert C. Martin
★★★★★
"Transformed how I think about naming, functions, and code organization."
Martin Kleppmann
★★★★★
"The best book on distributed systems fundamentals. Brilliant depth."
Ian Goodfellow, Yoshua Bengio, Aaron Courville
★★★★☆
"The foundational ML textbook. Dense but comprehensive."
Steven Skiena
★★★★★
"Best practical algorithms book I've read. War stories section is gold."
Have an opportunity, question, or just want to say hi? My inbox is open.
Whether you're a professor with a PhD opening, a recruiter with an exciting role, or a fellow researcher — I'd love to hear from you. I typically respond within 24 hours.