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AI Engineer with less than a year in Machine Learning & Generative AI
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Data Science professional with internship experience at Cognifiz Technologies. Skilled in Python, SQL, Power BI, Machine Learning, EDA, Statistical Analysis, Feature Engineering, and API Development. Seeking Data Analyst/Data Science/Machine Learning Engineer roles.
Cognifiz Technologies
Data Science Intern
October 1, 2025 – June 1, 2026
India
Customer Churn Prediction
June 5, 2026 – Present
Built end-to-end ML pipeline achieving 89% ROC-AUC, outperforming logistic regression baseline by 14%. Reduced false negatives by 22% through threshold tuning. Deployed model as FastAPI REST endpoint with sub-200ms inference latency.
PAN Card OCR System
June 5, 2026 – Present
Achieved mAP@50 of 99.1% with 98%+ per-class accuracy. Extracts Name, DOB, and PAN number in under 3 seconds via REST API. Engineered 4-step OCR preprocessing pipeline (LANCZOS upscaling, Otsu thresholding, Gaussian sharpening, denoising), improving name accuracy from 0% to 90%+. Deployed production FastAPI on Render with Swagger docs and Streamlit UI.
News Aggregator System
June 5, 2026 – Present
Developed AI-powered news aggregation platform with automated scraping and summarization. Implemented Retrieval-Augmented Generation (RAG) using vector embeddings. Integrated FastAPI backend with scalable architecture and structured storage.
Cultural Fit Analysis
The candidate's projects demonstrate a strong interest in AI/ML applications, aligning well with an AI Engineer role. The diversity of projects (OCR, churn prediction, news aggregation with RAG) indicates a broad curiosity and willingness to tackle different problem domains. The internship experience, while focused on data analysis, provides a good foundation for data-driven decision-making. However, the experience level is '0', indicating a junior profile, which might require more mentorship in a senior AI Engineer role.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a results-oriented approach and an ability to work on end-to-end solutions, from data preprocessing to deployment. Collaboration with cross-functional teams is mentioned in the internship, suggesting teamwork capabilities. However, without specific assessment data, a deeper analysis of soft skills like problem-solving under pressure or communication in complex scenarios is not possible.