Shivam Singha
Data ScientistAssam, IndiaMember since June 14, 2026
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
orthogonal-polyphase-codes
December 1, 2024 – December 1, 2024
orthogonal-polyphase-codes — GitHub repository
View Projectwild-edible-recognize
June 19, 2024 – July 9, 2024
wild-edible-recognize — GitHub repository
View Projectecommerce-spring
July 25, 2023 – November 20, 2023
An ecommerce web application built with Next.js and Spring Boot. The primary database used is PostgreSQL and Keycloak is used for ID and authentication.
View Projectaiot-food-storage
May 1, 2022 – September 24, 2023
An ML & IoT powered food storage monitoring system that enables real-time monitoring of temperature, humidity & CO2 and prediction of food spoilage. Achieved accuracy of 88% with SVM. It also features regular retraining of ML model to keep improving accuracy.
View Projecthardware-lab-verilog
September 19, 2021 – November 25, 2021
Verilog sources for Hardware Lab Assignments
View Projecttitanic-survival-predictor-react
April 10, 2021 – May 24, 2021
titanic-survival-predictor-react — GitHub repository
View Projectecommerce_backend1
December 17, 2020 – May 24, 2021
Full eCommerce backend. Written fully in TypeScript. Uses modern JWT auth, Prisma ORM and made secure.
View ProjectCultural Fit Analysis
The candidate's project portfolio shows a diverse range of technologies and interests, from web development (JavaScript, TypeScript, Java, Spring Boot, Next.js) to hardware (Verilog) and data science (Python, Jupyter Notebook, ML). While this breadth indicates curiosity and adaptability, the majority of projects are personal and lack explicit team collaboration or real-world impact beyond technical implementation. The alignment with a 'Data Scientist' role is present through specific ML projects, but the overall portfolio is quite broad, which could indicate a generalist profile rather than a deep specialization in data science. The lack of professional experience or education details makes it difficult to fully assess cultural fit.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions are concise, but there is no information on teamwork, problem-solving approaches, or communication style.