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AI ML Engineer with 2+ years in Data Science & Analytics
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AI Engineer and Data Science professional with 3+ years of experience building AI-powered analytics and automation solutions. Experienced in Python, FastAPI, RAG, LangChain, vector databases (FAISS), and LLMs including GPT-4o and Claude. Skilled in developing production-ready ML and GenAI applications, data pipelines, forecasting models, and AI-assisted document analysis systems. Passionate about building scalable AI products and agentic workflows that deliver measurable business impact.
ITM UNIVERSITY
B.TECH · COMPUTER SCIENCE
August 1, 2019 – June 30, 2023
AXION RAY
SENIOR ANALYST
March 1, 2024 – Present
Bengaluru, Karnataka, India
CAVISSON SYSTEMS
SOFTWARE ENGINEER
February 1, 2023 – February 1, 2024
Noida, Uttar Pradesh, India
AI-POWERED CUSTOMER RETENTION COPILOT
June 14, 2026 – Present
• Developed a customer retention analytics platform to identify high-risk customers and recommend targeted retention strategies. • Built churn prediction models using XGBoost and LightGBM, achieving ROC-AUC > 0.85; validated with stratified k-fold cross-validation to ensure generalisability. • Applied SHAP explainability to identify key drivers of customer churn and improve business understanding of customer behavior. • Integrated AI-powered recommendations using LLMs and retrieval-based knowledge systems to suggest retention actions. • Developed clean, modular FastAPI services and Streamlit dashboards to deliver insights and recommendations through an interactive interface.
View ProjectHackerRank SQL (Advanced)
HackerRank
June 1, 2026 – Present
AWS Global - Cloud Foundation
AWS
June 1, 2026 – Present
Data Analysis Using Python
Coursera
June 1, 2026 – Present
Microsoft Technology Associate - Intro to Python
Microsoft
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's experience spans analytics, AI/ML, and data engineering, showing a broad skill set relevant to a Data Science Engineer role. Their involvement in diverse projects (customer retention, document analysis, telemetry data analysis) and collaboration with various teams (senior data scientists, cross-functional, client stakeholders) suggests adaptability and a team-oriented mindset. The project diversity and skill breadth align well with a dynamic, data-driven environment.
Soft Skills & Operational Fit
The candidate demonstrates strong collaboration skills, evidenced by working with senior data scientists and cross-functional teams, contributing to improved project delivery rates, and partnering with client stakeholders. They also show initiative in owning end-to-end delivery of analytics and automation initiatives and defining project KPIs, indicating good operational fit and accountability.