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bp | ex-SITA
Data Scientist
June 21, 2026 – Present
automation-testing-on-cloud-infrastructure
June 13, 2025 – June 13, 2025
automation-testing-on-cloud-infrastructure — GitHub repository
View Projectskills-introduction-to-secret-scanning
May 23, 2025 – May 23, 2025
GitHub Skills: Introduction to Secret Scanning
View Projectconsumer_complaint
March 13, 2024 – March 13, 2024
consumer_complaint — GitHub repository
View ProjectConsumer-Complaint-Analysis
March 13, 2024 – March 13, 2024
Consumer-Complaint-Analysis — GitHub repository
View ProjectDiabetes-Prediction-AWS_BeanStalk
December 29, 2023 – December 29, 2023
project is a machine learning-driven application that uses Logistic Regression to assess the likelihood of an individual having diabetes based on their health metrics. Leveraging Python and Flask, this web-based tool provides an intuitive interface for users to input health data and receive predictions conveniently. Deployed on AWS BeanStalk
View ProjectFlipKart-Review-Scraper
September 25, 2023 – September 25, 2023
FlipKart-Review-Scraper is a powerful web scraping tool designed to extract and analyze customer reviews and ratings from Flipkart.
View ProjectSensorGuard-Pro
September 21, 2023 – March 30, 2024
In the world of heavy-duty vehicles, the reliability of critical systems like the APS is paramount. Unplanned failures can lead to downtime, costly repairs, and safety hazards. Our project addresses this challenge by building a machine learning model capable of distinguishing between APS-related failures and those caused by other factors.
View ProjectMySOP-Builder
September 21, 2023 – September 21, 2023
Statement of Purpose (SOP) Generator is a tool designed to assist students in creating compelling SOPs for university applications
View Projectkafka-pipeline
September 19, 2023 – February 27, 2024
This Confluent Kafka Pipeline project is designed to ingest data from sensors, process it using Kafka Streams, and then store the processed data in MongoDB. It provides a structured data pipeline for real-time data processing and storage.
View ProjectCultural Fit Analysis
The candidate's project portfolio shows a strong inclination towards personal projects, indicating self-motivation and a passion for learning and applying data science concepts. The projects cover various domains (finance, healthcare, e-commerce, industrial sensors), suggesting adaptability. However, the lack of team-based projects or contributions makes it difficult to fully assess cultural fit in a collaborative environment. The target role of 'Data Scientist' aligns well with the technical focus of the projects.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions indicate an ability to work on diverse technical challenges, but no direct assessment of collaboration, problem-solving, or communication in a team setting is available.