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Impact-driven Data Scientist with MLOps and AI expertise with 4 months of experience.
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Assessing your cultural and operational fit
Impact-driven Data Scientist experienced in building end-to-end ML systems using Python and SQL. Skilled in MLOps, explainable AI, and production deployment, with a focus on scalable, decision-ready models that drive business impact.
Sardar Patel Institute of Technology, Mumbai
Master of Computer Applications (MCA)
August 1, 2024 – June 30, 2026
Elphinstone College
Bachelor's in Information Technology (B.Sc IT)
August 1, 2021 – June 30, 2024
Unified Mentor Pvt. Ltd.
Data Science Intern
June 1, 2025 – September 1, 2025
India
Fraud Detection MLOps Pipeline
June 27, 2026 – Present
Developed and deployed a production-grade fraud detection system on highly imbalanced transaction data, optimizing precision-recall trade-offs to balance fraud capture and customer experience. Trained and tuned a cost-sensitive XGBoost classifier, applying appropriate evaluation strategies to avoid accuracy bias common in rare-event modeling. Integrated real-time explainability using SHAP to surface key feature drivers per transaction, supporting regulatory transparency and human-in-the-loop review. Built a reproducible, containerized MLOps pipeline with FastAPI, MLflow, Docker, and CI/CD to enable low-latency inference, experiment tracking, and safe production updates.
View ProjectChurn Prediction System (Hybrid Cloud)
June 27, 2026 – Present
Developed a churn prediction system modeling customer churn probability as a decision-support signal for targeted retention strategies. Engineered behavioral and lifecycle features and applied probability calibration to ensure reliable risk ranking across customer segments. Optimized classification thresholds under retention cost constraints, prioritizing high-impact customers within limited intervention budgets. Deployed a modular, full-stack ML application with a containerized backend and interactive frontend, ensuring scalable inference and clear separation of concerns.
View ProjectCultural Fit Analysis
The candidate's projects demonstrate a proactive approach to learning and applying diverse data science techniques, from fraud detection to churn prediction, and MLOps. The focus on building end-to-end systems and considering business impact aligns well with a results-oriented culture. The internship experience in an Agile environment further supports adaptability and teamwork. The breadth of technical skills listed, including Deep Learning and NLP/GenAI, suggests a continuous learning mindset.
Soft Skills & Operational Fit
The candidate demonstrates an ability to collaborate in Agile environments and translate analytical findings into business insights, indicating good operational fit. The project descriptions show a focus on business impact and decision-ready outputs, which aligns with practical application of data science. However, without specific assessment data on communication or psychometric traits, a deeper evaluation of soft skills is limited.