RS
CV
Open to SDE / data-focused roles

Rachit Singh —analytics-leddev building acrossweb, ML & APIs.

Full-stack and ML. Shipping clinic systems, training terrain classifiers, building AI apps, often all at once.

Book a call →Download CV
1000+Concurrent users
3ML case studies
78%ROI improvement
Rachit Singh, developer
Available for new projects
Open

01 — About me

Developer.
Researcher. Builder.

I shipped clinic booking flows and REST APIs at Novoguard, co-authored a peer-reviewed ML paper on satellite terrain classification, and built Prospera solo, a Gemini-powered career guidance platform used by thousands on launch.

I work across full-stack, ML, and data, not by spreading thin, but because the problems I keep getting pulled toward don't fit a single discipline. Looking for SDE and data-focused roles where that range is useful.

GitHub →LinkedIn →

02 — Featured work

Selected projects.

Three projects. Each one is live, each one has a number behind it.

Marketing Analytics & Campaign Optimization
PythonSQLAnalytics APITableau
78% ROI liftJan 2024

Marketing Analytics & Campaign Optimization

Problem

Marketing teams were flying blind, no unified view across channels, manual reporting, and ad budgets allocated on gut feel rather than data.

Built

Built a Python pipeline that ingested data from 10+ touchpoints (Google Ads, Meta, email, CRM) into a single analytics layer. Trained a marketing-mix ML model to attribute revenue to each channel and a lead-scoring model to rank inbound prospects.

Result

ROI improved by 78%. CTR/CPA/ROAS/LTV reporting went from weekly manual spreadsheets to automated daily dashboards. Sales team prioritised leads 3× faster using the scoring model.

Live demo →GitHub →
Prospera AI Career Guidance Platform
Next.jsGemini APITailwind CSS
1,000+ concurrent usersSep 2023

Prospera AI Career Guidance Platform

Problem

Students had no personalised career guidance tool; generic job boards and one-size-fits-all advice left them uncertain about paths, skills gaps, and opportunities.

Built

Designed and shipped a full-stack career counselling platform powered by the Gemini API. Built a real-time chatbot, personalised recommendation engine, and a responsive Next.js/Tailwind UI from scratch, solo, in under 6 weeks.

Result

Platform scaled to 1,000+ concurrent users on launch. Gemini-driven recommendations reduced average career decision time reported by test users by ~40%. Open-sourced on GitHub with active forks.

Live demo →GitHub →
Satellite Image Segmentation
PythonTensorFlowOpenCV
92% accuracy — +21 pts vs baselineMar 2024

Satellite Image Segmentation

Problem

Manual terrain analysis of satellite imagery is slow, expensive, and impractical at scale; existing open-source tools lacked accuracy for remote or low-resolution regions.

Built

Built a deep-learning pipeline using CNN/U-Net architecture with transfer learning and augmentation. Evaluated 4 model variants and selected U-Net after benchmarking against baseline segmentation accuracy of ~71%.

Result

Achieved 92% terrain classification accuracy, a 21-point improvement over baseline. Pipeline processes imagery in seconds vs hours of manual analysis, and is deployed as a public demo.

Live demo →GitHub →

03 — Where I've delivered

Experience.

Building production software at Novoguard and applying ML to real research.

Novoguard LLC (Verified Care)

Software Developer — Remote

Nov 2025 — Present

Certificate →
  • Rebuilt 4 core clinic booking flows from scratch using React, reduced form-completion steps by 40% and eliminated a class of drop-off errors reported by QA before handoff.
  • Designed and shipped 6 RESTful API endpoints (clinic search, filtering, auth, and profile) in Node.js; chose JWT over session-based auth to keep the service stateless and horizontally scalable.
  • Integrated Google Maps and a geolocation API to power proximity-based clinic discovery, replaced a manual city-dropdown with a live radius search, cutting average time-to-find-clinic by an estimated 3×.

04 — Publications

Research & papers.

Peer-reviewed work at the intersection of deep learning, remote sensing, and environmental monitoring.

Published · 2025

A Deep Learning Expedition Through Satellite Imagery for Environmental Insight

Feature extractionCNN
Global contextTransformer
Temporal dynamicsLSTM

Spatial feature maps from multi-band satellite imagery, extracting edges, textures, and spectral signatures across Landsat and Sentinel data.

95%Train accuracy

Long-range dependency modelling across image patches, capturing spatial relationships that local convolutions miss in complex terrain types.

92%Val. accuracy

Sequential change detection over time-series imagery, identifying environmental shifts in vegetation, water, and urban cover across seasons.

0.20Final train loss

Abstract

Presents a deep learning framework to extract high-resolution environmental insights from multispectral and hyperspectral satellite imagery sourced from Landsat, Sentinel, and commercial satellites. Integrates CNNs for spatial feature extraction, Transformer modules for long-range dependency modelling, and LSTM networks for temporal change detection across four land-cover classes.

Key contributions

  • CNN + Transformer + LSTM fusion for spatial, global, and temporal learning
  • Multi-sensor pipeline: Landsat, Sentinel, SAR, DEM, and meteorological fusion
  • Radiometric correction, cloud masking, augmentation, spectral normalisation
  • 4 land-cover classes: Water, Vegetation, Urban, Barren
95%Train accuracy
92%Val. accuracy
0.20Train loss
0.25Val. loss
20Epochs
4Classes
Megha Sharma1st AuthorRachit Singh2nd AuthorRachit Sharma3rd AuthorAbhishek Verma4th AuthorPragya GaurSupervisor
View full paper →

05 — Expertise

Stack.

What I reach for first.

JavaScript / React / Next.jsTypeScriptTailwind CSSNode.js & REST APIsPython (Pandas, NumPy)TensorFlow / Keras / CNNSQL (MySQL)MongoDBGoogle Analytics APITableau / MatplotlibOpenCVFastAPI / Celery / RedisDockerGit & CI/CDJava
JavaScript / React / Next.jsTypeScriptTailwind CSSNode.js & REST APIsPython (Pandas, NumPy)TensorFlow / Keras / CNNSQL (MySQL)MongoDBGoogle Analytics APITableau / MatplotlibOpenCVFastAPI / Celery / RedisDockerGit & CI/CDJava

06 — Thoughts & writing

Recent articles.

Practical write-ups on React patterns, front-end architecture, and the problems I actually ran into building real projects.

01
TutorialReact · Front-end

Create a Loading Screen in React

Most React apps skip the loading state entirely. Users stare at a blank white screen for half a second before content snaps in. This guide walks through building a polished, animated loading screen using a simple boolean state flag, CSS keyframe animations, and a useEffect cleanup pattern that prevents the dreaded flash on fast connections.

Mar 20245 min read
02
Deep DiveReact · Patterns

Form Validation with Custom Hooks

Repeating validation logic across every form in a codebase is a maintenance nightmare. This article extracts the full validation lifecycle: touched state, error messages, async field checks, and submit locking, into a single reusable useForm hook.

May 20248 min read
03
PatternReact · UI

Pagination Component Patterns

Pagination is deceptively tricky: ellipsis logic, edge-case handling, accessible keyboard navigation, and URL-synced state all need to work together. This breakdown covers three patterns, offset-based, cursor-based, and infinite scroll, with trade-offs for each.

Aug 20247 min read

07 — Verified proof

The work is public.

Certificate, paper, source code. Everything below links to the actual thing.

Certificate of Experience

Novoguard LLC (Verified Care)

Ongoing Software Developer engagement at Novoguard LLC (Verified Care) since Nov 2025. Covers contributions to clinic booking flows, REST API development, and geolocation integration on the Verified Care platform.

Remote · Nov 2025 – PresentOpen certificate
Published Research

Conference Paper

"A Deep Learning Expedition Through Satellite Imagery for Environmental Insight." Co-authored with 4 peers and a faculty supervisor. 95% training / 92% validation accuracy across 20 epochs, 4 land-cover classes.

5 authors · 2025Read paper
Open Source

Prospera AI GitHub

Full source for the Gemini-powered career guidance platform: publicly auditable code, commit history, and architecture. Built solo in under 6 weeks, handling 1,000+ concurrent users on launch.

Next.js · Gemini API · TailwindView repository
2Companies
1000+Concurrent users
92%Model accuracy
78%ROI improvement
5Research co-authors

08 — Let's build

Let's work
together.

Looking for full-time SDE and ML roles, and open to freelance contracts. I reply same day.

Email me →Schedule a call
Emailrachitdude008@gmail.com
GitHubgithub.com/devxrachit
LinkedInrachit-singh-471491258
LocationIndia, Asia — IST