Technical Arsenal
Tools & Technologies
The stack I use to explore data and engineer solutions.
Bhargav Kumar Nath.
Data Scientist & ML Engineer.
Available for full-time work
Building predictive models on millions of real-world records, seamlessly bridging the gap between raw data pipelines and deployed ML systems.
bhargav@ml-cluster ~
$system-status --live
>
ALL SYSTEMS NOMINAL|GPU: 94% util|Uptime: 847d
4.5×
Conversion Uplift
£0.139
Forecasting MAE
<1ms
Inference Latency
8–32×
Serving Throughput
40%
VRAM Reduction
100M+
Event Pipeline
About Me
Researcher who ships
production systems.
I hold an MSc in Data Science and Analytics from the University of Leeds and a BTech in Computer Science and Engineering from Assam Don Bosco University. My expertise bridges Machine Learning and Software Engineering: not just building models, but deploying and scaling them reliably.
I specialize in predictive modeling, deep learning architectures, and end-to-end MLOps pipelines. From processing datasets exceeding 100 million records using PySpark to deploying high-performance inference engines, I focus on unlocking tangible value through robust data ecosystems.
Current Focus Areas
Building scalable prediction systems
Natural Language Processing & LLMs
Real-time analytics & streaming pipelines
Bridging data science research and production engineering
MSc
Data Science & Analytics, Leeds
~2
Years professional experience
11
End-to-end ML projects shipped
Philosophy
"A model is a mathematical fantasy, but an ML system is a living entity. I design for the shifting reality of the human world, not the static perfection of a laboratory."
01
Escape the State-of-the-Art Trap
Leaderboard victories rarely survive reality. I start with the simplest model to establish an honest baseline and prove if building ML is even necessary.
02
Algorithms Fade, Data is Foundational
Architectures change but long-term success depends on data quality. Real-world data is noisy and evolving; inflexible systems quickly become obsolete.
03
Deployment is the Starting Line
Standard software fails loudly, but ML systems fail silently via confident incorrect predictions. Production models need continuous monitoring to stay reliable.
Proof of Work
Data Science & ML Projects
Demonstrating end-to-end expertise uniting predictive modeling with resilient MLOps.
Engineering Track
Experience & Education
A track record of engineering impact across institutions.
Professional Engineering
M/S Sanjog TradingGuwahati, India
Jul 2020 to Nov 2021End-to-End ETL Infrastructure
Architected Python ETL pipelines using Pandas & NumPy, eliminating manual processing bottlenecks and establishing reliable data infrastructure for downstream ML.
Predictive Forecasting System
Developed and validated statistical time-series forecasting models for daily/monthly sales trends, enabling algorithmic inventory planning and supply chain optimization.
Real-Time BI Dashboard
Engineered interactive Streamlit dashboards to visualize sales KPIs, seasonal trends, and performance metrics, enabling live data-driven pricing strategies.
IIT GuwahatiGuwahati, India
Jul 2022 to Aug 2022Relational Database Architecture
Designed normalized MySQL schemas with optimized indexing for ACID-compliant data integrity across 15+ frontend modules.
Constraint-Satisfaction Optimization
Conceptualized a heuristic constraint-satisfaction algorithm for automated timetable generation, foundational to operations research and resource-allocation ML.
Evidence-Based UX Research
Conducted structured quantitative user research across multiple institutions and performed competitive feature analysis of 4 EdTech platforms.
Airports Authority of IndiaNER Regional HQ, India
Jul 2023 to Aug 2023Enterprise Asset Analytics
Analysed operational data for 1,053+ IT assets through an enterprise Asset Management System, tracking deployment status, warranty lifecycles, and maintenance history.
SAP ERP Data Workflows
Documented cross-functional SAP ERP workflows covering HR, Finance, and Procurement, gaining hands-on exposure to enterprise ETL architecture and data governance.
Network Infrastructure Mapping
Mapped enterprise network infrastructure including MPLS/ILL load balancing, core switching, and firewall architectures, critical for production MLOps deployment.
Academic Foundations
Sep 2024 to Nov 2025
MSc Data Science and Analytics
University of Leeds, UK
Specialized in advanced machine learning, predictive modeling, data mining, and big data architecture. Developed expertise in end-to-end data pipelines, real-time analytics, and MLOps principles.
Aug 2020 to Jun 2024
BTech Computer Science and Engineering
Assam Don Bosco University, India
Solid foundation in software engineering, algorithms, data structures, and database management. Led projects integrating classical software design with early predictive modeling applications.
Key Capabilities
Agentic AI Workflows
MLOps & ResOps
High-Performance Computing
Quantitative Research
End-to-End ML Pipelines
LLM Inference Optimization
Writing
Published Articles
Exploring algorithms, trends, and the intersection of technology, AI research, and society.
Deep Learning Lab
A dependency-free Mathematical Engine built in TypeScript. Experiment with hyperparameters, inject live training noise, and compare train/test behavior in real-time.