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Data Science with less than a year in ETL pipelines, data quality, and AI/ML applications.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
M.Sc. Computer Science student with hands-on experience building ETL pipelines, validation systems, and AI-integrated applications. Proficient in Python, SQL, and data extraction/transformation with a strong eye for data quality. Enthusiastic fresher ready to work on real-world data analytics projects, collaborate with experienced professionals, and develop analytical & problem-solving skills in a remote full-time role. Immediate joiner – available from Day 1.
Utkal University
M.Sc. · Computer Science
September 1, 2024 – Present
Gayatri +3 Science College
B.Sc. · Computer Science
September 1, 2021 – May 1, 2024
Automated ETL Data Pipeline with Validation & Reporting
January 1, 2023 – June 1, 2024
Designed a batch ETL pipeline extracting structured data from CSV/JSON sources, applying transformation rules (deduplication, type casting, null handling), and loading clean records into PostgreSQL - directly mirroring data analytics associate workflows. Built a multi-stage validation layer to enforce schema constraints, flag anomalous records, and generate data quality summary reports ensuring accuracy across all processed data. Automated execution with scheduling logic and exception-handling error logs, enabling traceable high-volume data processing with consistent SLA adherence.
Geospatial & Structured Data Aggregation Platform (Mealithic)
January 1, 2023 – June 1, 2024
Built a data ingestion system aggregating records from multiple external APIs with rule-based multi-stage validation (classification, normalisation, constraint checking) - closely aligned with real-world analytics workflows. Developed REST API endpoints with response caching to serve validated data to a frontend, reducing redundant queries and improving data delivery efficiency across teams.
Biometric Data Processing & Verification System
January 1, 2023 – June 1, 2024
Engineered a real-time data processing pipeline capturing, processing, and storing structured feature vectors for high-volume identity verification end-to-end data flow experience. Applied OOP design patterns for modular components across data capture, feature extraction, and validation; integrated Python backend with Node.js API for smooth cross-functional communication.
The candidate scored 0% on this test, indicating a complete lack of proficiency in Data Science and Artificial Intelligence, which is a critical skill for the target role.
Limitations
The candidate scored 100% on this test, showing excellent knowledge and practical understanding of Azure Data Engineering, including Databricks DLT, streaming, and cost management.
Cultural Fit Analysis
The candidate's academic projects demonstrate a proactive approach to learning and applying data-related skills. The interest in open-source data tools, automation scripting, and continuous learning aligns with a growth-oriented culture. However, the target role is 'Data Science,' while the candidate's strongest technical scores are in 'Data Engineering.' This misalignment suggests a potential gap in direct cultural fit for a pure Data Science role, though the data engineering skills are highly transferable and valuable.
Soft Skills & Operational Fit
The candidate's resume highlights an analytical mindset, fast learning ability, strong communication, and a solution-first approach. The psychometric test score of 299/500 suggests average performance in areas like logical reasoning, work attitude, stress handling, and team collaboration. The English test score of 57/100 indicates room for improvement in communication clarity and professional language usage, which could impact cross-functional collaboration.
Strengths
The candidate scored 100% on this test, indicating a comprehensive understanding of core data engineering principles and data platform architectures.
Strengths