VAVansh Agarwal
DATA SCIENCE / MACHINE LEARNING / ANALYTICS

From complex data.
To clear decisions.

I’m Vansh, a data science and machine learning professional. I build predictive models, reliable pipelines, and analytics that turn business questions into practical answers.

Explore my work 03
MSc Business Analytics · Nanyang Technological UniversityPython · SQL · Machine Learning
01 / SELECTED WORK

Applied to real problems.

From inventory operations to financial signals and information retrieval.

01
SUPPLY CHAIN / COMPUTER VISION

Extinguish

A B2B supply chain application bringing real-time inventory logging and computer vision into inventory audits.

SwiftTensorFlowOpenCVDBMS
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The challenge

Reduce the manual effort and reconciliation errors involved in tracking inventory.

My approach

Combined real-time logging with computer vision for inventory audits, supported by KPI tracking, data validation, and documented system flows.

Reported outcome

60% fewer reconciliation errors and 11% fewer stockouts.

60%

fewer reconciliation errors

Inventory audit automation
02
FINANCE / TIME SERIES

Business valuation
& stock prediction

A forecasting workflow connecting financial valuation, time-series models, and news sentiment.

PythonARIMALSTMPandas
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The challenge

Bring business fundamentals and time-series patterns into one analytical workflow.

My approach

Built ARIMA models for quarterly forecasts and LSTM models for longer-horizon patterns. Integrated discounted cash flow logic and sentiment features, with dashboards for performance and risk metrics.

Focus

Forecast evaluation, financial modelling, and clear communication of model outputs.

DCF + ML

Fundamentals meet forecasting

Valuation · Time series · Sentiment
03
NLP / INFORMATION RETRIEVAL

Document retrieval
accelerator

An NLP pipeline designed to find relevant information faster and reduce manual document review.

PythonNLPVectorizationRanking
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The challenge

Make semi-structured document collections easier to search and review.

My approach

Implemented text preprocessing, vectorization, and ranking. Evaluated the workflow using precision, recall, and latency to balance relevance with speed.

Reported outcome

30% less manual review effort, with document retrieval accelerated by 25% during my Wise Work internship.

30%

less manual review effort

Information retrieval with NLP
02 / EXPERIENCE

Built through practice.

Internships across analytics, machine learning, application development, and data engineering.

FEB — MAY 2024

Skillcase

Project Management Intern · Data Insights

Used experiments and performance metrics to increase lead generation by 50%. Optimized SQL workflows to reduce report latency by 30%.

Business analytics
FEB — DEC 2023

Wise Work

Machine Learning Intern

Built NLP pipelines for faster document retrieval and automated ETL across five data sources, with schema validation and monitoring.

Applied ML
APR — MAY 2023

Infosys

iOS Application Development Intern

Developed a hospital database application handling 10,000+ records, alongside Swift interfaces and Tableau reporting.

Application development
FEB — APR 2023

Aaseya IT Services

Data Analyst Intern

Worked on Amazon Kinesis ingestion for 2M+ daily events. Automated Python ETL to reduce downstream latency by 35%.

Data engineering
03 / ABOUT

Analytical by training.
Curious by nature.

My background combines computer science and AI with business analytics. I enjoy working across the full data lifecycle—from ingestion and validation to modelling and explaining what the results mean.

Beyond data, I play guitar and have competed in abacus at the national level. Both keep me practicing a balance of precision and creativity.

Connect on LinkedIn

Education

2024 — 2025

MSc, Business Analytics

Nanyang Business School
Nanyang Technological University, Singapore

GPA 4.52 / 5.0
2020 — 2024

BTech, Computer Science & Engineering

Specialisation in AI & ML
SRM Institute of Science and Technology, India

CGPA 8.88 / 10.0

My toolkit

PythonSQLRScikit-learnTensorFlowPyTorchTableauPower BIGitAmazon Kinesis
04 / GET IN TOUCH

Have a problem
worth exploring?

Let’s talk data, machine learning,
and what we could build together.