Rolling Array

Data Scientist

https://talent.gravityer.com/rolling-array

Rolling Array :: We Create Useful Tools !

IndiaMember since June 14, 2026

Key Strengths

Demonstrated interest in Data Science and AI/ML through multiple personal projects.
Experience with Python, Jupyter Notebook, and relevant libraries for data science tasks.
Projects like 'KafkaNeuroPredict' show practical application of deep learning and real-time data processing.
Exposure to federated learning ('FedLearn-Lite', 'tapnet-federated') indicates interest in advanced ML paradigms.
Project 'Cortex' highlights experience with AI-powered platforms and transforming unstructured data.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects are primarily personal and demonstrate a strong interest in AI/ML and data science. However, the lack of professional experience or team-based projects makes it difficult to assess cultural fit in a corporate environment. The diversity of projects, including web development technologies, suggests a broad technical curiosity, but the core focus aligns well with a Data Scientist role.

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.

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Projects

Cortex

June 2, 2026 – Present

Cortex is an AI-powered knowledge and reasoning platform designed to transform unstructured information into actionable intelligence.

View Project

transformer-learning-lab

April 23, 2026 – Present

transformer-learning-lab — GitHub repository

View Project

Books

April 21, 2026 – Present

Books — GitHub repository

View Project

tapnet-federated

July 18, 2025 – November 25, 2025

tapnet-federated — GitHub repository

View Project

FedLearn-Lite

July 17, 2025 – July 18, 2025

Federated Learning for Linear Regression

View Project

Synthetic-Data-Generator

June 29, 2025 – June 29, 2025

Synthetic-Data-Generator — GitHub repository

View Project

KafkaNeuroPredict

February 28, 2025 – February 28, 2025

Real-time stock price prediction system that leverages Kafka streaming, TensorFlow deep learning models, and Python to analyze and predict stock prices. The system consumes live stock data, processes it through a trained neural network model, and publishes predicted prices.

View Project

Sports-Performance-Analysis-using-YOLOV4-Kalman-filter

February 20, 2025 – May 21, 2025

Sports-Performance-Analysis-using-YOLOV4-Kalman-filter — GitHub repository

View Project

Enterprise-ionic-monorepo

May 1, 2022 – May 5, 2022

Enterprise-ionic-monorepo — GitHub repository

View Project

C2-server-api

April 21, 2021 – January 7, 2022

This is the server api repo for C2. C2 is a platform designed to nullify any bias in terms of race, age, gender, disability and culture when treating a workforce and provide measurable matrix for a best fit person to grab a new opportunities

View Project

Key Strengths

Demonstrated interest in Data Science and AI/ML through multiple personal projects.
Experience with Python, Jupyter Notebook, and relevant libraries for data science tasks.
Projects like 'KafkaNeuroPredict' show practical application of deep learning and real-time data processing.
Exposure to federated learning ('FedLearn-Lite', 'tapnet-federated') indicates interest in advanced ML paradigms.
Project 'Cortex' highlights experience with AI-powered platforms and transforming unstructured data.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.

Rolling Array

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Projects

Key Strengths

Cultural & Operational Fit