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🕐 - · Coimbatore, IN

Hello, I'm

Shanjai R

Data Scientist - E-commerce & Market Intelligence

Software Engineer II at PromptCloud / 42Signals · M.Tech Data Science, BITS Pilani

Data Science · Analytics · Data Engineering · E-commerce Intelligence

Currently Building SARA: a fashion & retail intelligence pipeline

11.0168°N · 76.9558°E
Shanjai R
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01 About

About Me

I work where messy data meets real-world systems.

RoleSoftware Engineer II
CompanyPromptCloud / 42Signals
LocationCoimbatore, India
LanguagesTamil · English

As a data scientist, my work sits across data engineering, analytics and e-commerce intelligence - building pipelines, processing systems and analytical workflows that turn raw marketplace and web data into something teams can actually use, including SARA, my current work in fashion and retail intelligence.

Over the last few years, I have worked across data collection, processing, validation, infrastructure, analytics and intelligence systems - a perspective that sits somewhere between engineering and problem-solving. I'm currently expanding that foundation through my M.Tech in Data Science at BITS Pilani.

What I'm Building Now Updated Aug 2026
💼
Currently Working On Turning raw marketplace and web data into market intelligence, competitor analysis, pricing signals and search intelligence
🎓
Currently Studying M.Tech Data Science coursework at BITS Pilani
🔭
Currently Exploring LLM-powered data extraction, intelligent data pipelines and AI-assisted market intelligence
📖
Currently Reading Designing Data-Intensive Applications, by Martin Kleppmann
Current Focus Areas

Data ScienceMachine LearningE-commerce IntelligenceData InfrastructureCompetitor IntelligenceData-Driven Decision SystemsAI-Assisted Analytics

✦ My Journey

The Story Behind the Work

2020

Started B.Tech IT

Began Information Technology at Sri Shakthi Institute of Engineering and Technology without a clear idea of where it would lead. Graduated in 2024 with 8.58 CGPA, First Class with Distinction.

2023

Joined PromptCloud as an Intern

Worked on banner placement analysis for Amazon, Nykaa, and Blinkit, and discovered a real interest in working with real-world, messy data rather than textbook problems.

2024

Moved Into Software Engineering

Became an Associate Software Engineer and began owning production data pipelines: the Client Site Mapping Dashboard for 42Signals and a modular, YAML-driven web scraping pipeline.

2025

Took on Product Ownership, Started M.Tech

Promoted to Software Engineer I with full ownership of 42Signals product operations, and enrolled in M.Tech Data Science and Engineering at BITS Pilani.

2026

Promoted to Software Engineer II

Continuing to move from operational execution toward data science, analytics and intelligence: competitor, price and search intelligence systems built on that engineering foundation.

● Now

Mentoring & Still Building

Conducting mock interviews for college juniors: resumes, Python, logical thinking. Because guidance matters enormously at the start. And for me, this is only the beginning.

🎯

My Vision

Build systems that solve real problems people actually face, not just what looks impressive. Clarity, structure, and long-term impact over short-term noise.

🚀

My Mission

Take ownership. Refine until it's right. Grow into someone who doesn't just contribute, but leads, shapes outcomes, and makes things meaningfully better.

02 Experience

Where I've Worked

2026 – Present

Software Engineer II

PromptCloud / 42Signals · Bengaluru

Data Engineering · E-commerce Intelligence · Automation · Analytics

I work across data engineering, analytics and e-commerce intelligence, turning raw marketplace and web data into systems that support business decisions.

  • Own data workflows supporting competitor intelligence, pricing intelligence, search intelligence and marketplace analytics.
  • Investigate data-quality failures across collection, processing, validation and downstream analytics.
  • Translate ambiguous client and product problems into data requirements, analytical workflows and engineering improvements.
  • Work across engineering, product, analytics and business contexts to understand how data should influence decisions.
  • Verified impact: separating two workflows that had been conflated due to an outdated client requirement cut analytics cost by roughly 50%. SARA, the retrieval architecture underneath this work, is applied across 22 fashion e-commerce and media sites.
PythonData AnalysisElasticsearchKibanaMySQL
2025 – 2026

Software Engineer I

PromptCloud / 42Signals · Bengaluru

Data Engineering · Analytics Pipelines

Worked at the intersection of data engineering, analytics and e-commerce intelligence, converting raw web and app data into structured datasets used for business analysis.

  • Built automated validation and quality checks to identify anomalies and unreliable data.
  • Defined and improved data-quality standards across workflows and teams.
  • Developed analytical systems covering competitor movement, pricing and search visibility.
  • Worked with client requirements to determine which data was actually useful, rather than simply collecting more.
  • Selected work: Competitor Intelligence, Price Intelligence, Search Intelligence and Product Matching.
PythonData AnalysisElasticsearchKibanaMySQL
2024

Associate Software Engineer

PromptCloud · Bengaluru

Systems Design · Data Pipelines

Designed modular data pipelines for collection, fetching, extraction and validation, applying statistical techniques to support business decisions.

  • Built configurable extraction workflows using Python, YAML and MySQL.
  • Worked with large and inconsistent web datasets where schema and page structures varied across sources.
  • Improved pipeline reliability through reusable components and validation layers.
  • Investigated failures at the data and pipeline level, rather than treating extraction errors as isolated incidents.
PythonBeautifulSoupScrapyMySQL
2023 – 2024

Software Engineering Intern

PromptCloud · Bengaluru

Web Scraping · Data Extraction

Built configurable web-data extraction systems for production workflows, supporting market research and content aggregation projects.

  • Worked with pagination, content fetching, HTML parsing, XPath and site-specific extraction rules.
  • Learned to work with unreliable external data sources and changing website structures.
PythonRubyBeautifulSoupNokogiriXPath

03 Skills

Technical Toolbox

Current Focus · Applied Data Science for Market Intelligence - exploring statistical methods, machine learning and AI-assisted approaches for extracting signal from large-scale marketplace and web data

Data Science & Analytics

PythonPandasNumPyData AnalysisData ScienceCompetitive IntelligencePrice IntelligenceSearch IntelligenceMarket IntelligenceE-commerce Analytics

Data Engineering

SQLMySQLETLData PipelinesData ProcessingData QualityElasticsearchRabbitMQDistributed Processing

Machine Learning & AI

Machine LearningLLMsLangChainHugging FaceOpenAI

Development & Data Systems

GitLinuxDockerJavaScriptHTMLXPathDOMBeautifulSoupRequests

04 Education

Academic Background

🎓

M.Tech Data Science and Engineering

Birla Institute of Technology and Science, Pilani

Oct 2025 – Aug 2027 Current CGPA: 8.58
🎓

B.Tech Information Technology

Sri Shakthi Institute of Engineering and Technology

Nov 2020 – Apr 2024 CGPA: 8.58  ·  First Class with Distinction

05 Recognition

Awards & Honours

🚀 ×1

Emerging Leader

Awarded for impeccable ownership of the 42signals product, driving multiple client engagements, leading new explorations, and demonstrating strong leadership initiative.

🏆 ×2

Stretch Award

Recognized for going above and beyond on key projects, consistently exceeding expectations and delivery targets.

⭐ ×5

Hi5 Award

Celebrated for exceptional teamwork, collaboration, and sustained positive impact across cross-functional teams.

06 Selected Work

Selected Work

Marketplace Collection
Normalization
Competitor Mapping
Dashboard & Alerts
01

Competitor Intelligence Engine

Competitor Analysis · E-commerce Market Intelligence

PromptCloud / 42Signals
Problem

A manually maintained competitor list goes stale the moment it's written down.

Approach

Continuously track pricing, assortment and positioning, scoring how confident each match is.

System

Shown above as a 4-stage pipeline; hover a stage to see what it does.

Outcome

Competitive visibility becomes a dashboard checked regularly, not a project someone has to remember to run.

PythonElasticsearchKibanaMySQL
Read the Case Study
Data Ingestion
Data Standardization
Product Mapping
02

Price Intelligence & Revenue Leakage Detection

Demand Signals · Pricing

PromptCloud / 42Signals

A marketplace pricing intelligence workflow designed to identify meaningful price discrepancies while reducing noise from irrelevant or low-value data fields.

Outcome: pricing anomalies surface as they happen, not as a quarterly surprise.

PythonMySQLElasticsearch
Read the Case Study
Search & Category Crawl
Keyword-Level Ranking
Visibility Scoring
03

Search Intelligence & Brand Visibility Analytics

Search & Keyword Insights

PromptCloud / 42Signals

A search-performance intelligence system covering keyword rankings, brand visibility, competitor movement, rank distribution and product-level performance.

Outcome: visibility becomes a number tracked over time, not a vague sense of underperformance.

PythonKibanaData Analysis
Read the Case Study
Input · SKU Master
Search & Discovery
Extraction & Matching
04

Automated Product Matching Pipeline

Fashion Retail Client · Digital Shelf Analytics

PromptCloud / 42Signals

A system for connecting products across marketplaces using product attributes and similarity signals to improve cross-market analysis.

Outcome: when the system isn't confident two listings are the same product, it says so, rather than guessing.

PythonData ValidationElasticsearch
Read the Case Study
Discovery
Retrieval
Parsing
05

SARA

Data Engineering Foundation · Scalable Automated Retrieval Architecture

Currently Building

The reusable retrieval architecture behind the intelligence systems above: collection, fetching, extraction, validation and downstream processing, applied across 22 fashion e-commerce and media sites and indexed into Elasticsearch.

PythonRabbitMQElasticsearchFastAPIAPScheduler
Read the Case Study
URL Collector
Page Fetcher
YAML Parser
06

Modular Web Scraping Pipeline

PythonMySQLBeautifulSoup

A modular pipeline for URL collection, fetching and rule-based extraction using Python, YAML, MySQL, CSV and web parsing components - the engineering foundation this career has been built on.

Outcome: onboarding a new source became a configuration change, not a rewrite: the same principle SARA later scaled further.

Read the Case Study
View All Projects

07 Writing

Notes & Observations

The Person Who Knows How the Company Works Has More Leverage Than the Person Who Knows the Most

The Person Who Knows How the Company Works Has More Leverage Than the Person Who Knows the Most

Understanding why a system was built a certain way is worth more than knowing the most code. Two pipelines that looked logically separate turned out to be split only because of an outdated client requirement; recognizing that led to roughly a 50% reduction in analytics cost. "The code tells you what. The history tells you why."

The Deepest Peace is Found in Chaos

The Deepest Peace is Found in Chaos

Society romanticizes peace as quiet beaches and minimalist spaces, but the real thing is different. Coming home during festivals, chaotic and loud as it is, produces a calm no silence ever could. "Peace is not the absence of noise. Peace is the presence of a safety net."

The Art of Poking Around

The Art of Poking Around: How Curiosity Made Me a Better Engineer

Responsibility defines deliverables. Curiosity drives growth. Poking around a product beyond what's assigned (every dashboard, filter, and edge case) surfaces problems raw data never shows on its own. "The most valuable engineering skill isn't writing better code. It's being curious enough to keep poking around."

A Watchtower Without a Watchman Is Just Architecture

A Watchtower Without a Watchman Is Just Architecture

Every dashboard, alert, and automation you build adds a system, and every system needs an owner, or it just becomes hidden risk. "A watchtower without a watchman is just architecture. A dashboard without an owner is just a chart."

Security Is Not Living Inside an Iron Dome

Security Is Not Living Inside an Iron Dome

Repeatedly firefighting the same emergencies is a design problem, not an effort problem. Real strength isn't living inside an iron dome of manual fixes and constant monitoring; it's building systems that stay stable as complexity grows. "Security is not just protection. It is resilience by design."

✦ Beyond Work

When I'm Not Coding

✈️

Travel

Chasing sunsets in Poovar, palace views in Udaipur: experiences that shift perspective more than any textbook ever could.

Poovar IslandUdaipurMore coming
📸

Photography

Capturing candid moments and landscapes. Every frame holds a memory worth keeping.

🎓

Mentoring

Mock interviews for college juniors: resumes, Python, logical thinking. Giving back what I wish I had at the start.

10+ sessions
🎵

Music I Love

Artists & songs
Group BTS K-pop
Solo Shreya Ghoshal Bollywood
All-time fav 🔁 GO GO BTS
Current fav NORMAL BTS

10 Contact

Get In Touch

Working on a data problem?

Building a data pipeline, analytics system, market intelligence product, or something somewhere between them? I'd be interested in understanding the problem.

Ready to collaborate?

Say Hello

Drop me an email and I'll get back to you within 24 hours.

Send a Message
✉
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