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Data Science with less than a year in Python, SQL & Cloud
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
B.Tech CSE graduate with strong Python, database, and data engineering skills. Built platforms processing 10,000+ records with MongoDB, PostgreSQL, and MySQL. Experienced in REST APIs, data annotation pipelines, and AWS cloud infrastructure. Analytical mindset with attention to data quality and system design.
100xDevs
Bootcamp · Full Stack & Web3
November 1, 2024 – November 1, 2025
Dr. Babasaheb Ambedkar Technological University
B.Tech · Computer Science & Engineering
October 1, 2021 – July 1, 2025
CodeSoft
Web Development Intern
February 1, 2024 – March 1, 2024
Pune, Maharashtra, India
TURKYFY – Data Annotation & Quality Assurance Platform
July 1, 2025 – June 1, 2026
Built a crowdsourced data labeling platform — collects, validates, and structures human-annotated datasets for AI/ML training; directly mirrors S&P Global's data quality operations. Implemented response validation logic, data deduplication, and structured storage in MongoDB; designed task distribution ensuring consistent, high-quality labeled data output. Automated payment and task tracking workflows — generating structured data reports for reviewer performance analytics.
Python Data Pipeline - Automated ETL & Reporting System
January 1, 2025 – March 1, 2025
Built an ETL pipeline using Python (Pandas) to extract data from REST APIs, clean/transform records, and load structured output into PostgreSQL for downstream analysis. Automated report generation with Matplotlib visualizations — produced weekly data summaries covering key trends, anomalies, and KPI tracking. Stored processed datasets on AWS S3 for archival; implemented logging and error-handling to ensure data integrity throughout the pipeline.
Data Analytics Dashboard - Medical Records & Appointment Insights
October 1, 2024 – May 1, 2025
Built a full-stack healthcare platform processing 10,000+ labeled medical image records — managed data ingestion, storage, cleaning, and structured retrieval pipelines. Developed AI diagnostic model (93% accuracy) by training on large-scale labeled datasets; designed data collection, annotation, and validation workflows end-to-end. Created RESTful APIs for structured data access across Admin, Doctor, and Patient roles — generated appointment trend reports and patient record analytics via dashboard.
Cultural Fit Analysis
The candidate's projects show a strong inclination towards practical, hands-on development in data science and analytics. The 'TURKYFY' project, mirroring S&P Global's data quality operations, indicates an awareness of industry best practices and a drive to build robust systems. The range of technologies used across projects (Python, Node.js, various databases, AWS) suggests adaptability and a willingness to learn new tools. However, the experience level is entry-level, which might require mentorship for a senior role.
Soft Skills & Operational Fit
The candidate demonstrates an analytical mindset with attention to data quality and system design, as evidenced by their project descriptions. Their experience in building end-to-end data workflows suggests a methodical approach to problem-solving. The project diversity indicates an ability to work on different aspects of data science, from data engineering to model development and visualization.