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AI Engineer with 3+ years in Data Analytics & Cloud Solutions
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Assessing your cultural and operational fit
Data-driven professional with 3 years of hands-on experience in data analytics, process optimization, and operational excellence in large-scale industrial environments. Currently building ML expertise with focus on Python, SQL, AWS, and ML fundamentals. Skilled in designing and deploying ETL pipelines, cloud-based data solutions, and automation projects using AWS (S3, Glue, Lambda, DynamoDB). Certified in AWS Cloud and Data Analytics. Passionate about leveraging data-driven insights and ML algorithms to solve real-world business problems. Quick learner with strong problem-solving abilities and commitment to continuous growth in AI/ML technologies.
G H Raisoni College of Engineering, Nagpur
B.E. · Electrical Engineering
August 1, 2018 – June 30, 2022
JSW Cement & BMM ISPAT
External Consultant
September 1, 2025 – Present
India
JSW
Maintenance Analyst
August 1, 2022 – August 1, 2025
India
Enterprise Knowledge Assistant
January 1, 2025 – December 31, 2025
Developed an AI assistant for answering questions from business documents. Stored and managed documents using AWS S3. Built APIs using FastAPI for user interaction. Improved information accessibility through conversational search.
House Price Prediction System
January 1, 2025 – December 31, 2025
Developed a machine learning model to predict house prices based on features such as area, number of bedrooms, bathrooms, and location. Performed data cleaning, missing value handling, and feature selection. Conducted Exploratory Data Analysis (EDA) using Pandas and Matplotlib. Trained and evaluated a Linear Regression model using R² Score and Mean Absolute Error (MAE). Visualized actual vs predicted house prices for model evaluation.
S3 to DynamoDB Serverless Ingestion Pipeline
January 1, 2025 – December 31, 2025
Developed a serverless ingestion pipeline triggered automatically by S3 uploads. Processed and inserted records into DynamoDB using Lambda functions. Implemented IAM-based access controls for secure data processing.
Employee Salary Prediction System
January 1, 2025 – December 31, 2025
Built a machine learning model using Linear Regression to predict employee salaries based on years of experience. Performed data preprocessing and feature engineering. Evaluated model performance using MAE and R² Score. Visualized predictions using Matplotlib.
PostgreSQL to AWS S3 ETL Pipeline
January 1, 2025 – December 31, 2025
Built an automated ETL pipeline to transfer data from PostgreSQL to Amazon S3. Implemented data validation, error handling, and date-based partitioning. Developed reusable Python scripts for scalable data migration workflows.
FGD NE System Availability Enhancement
January 1, 2025 – December 31, 2025
Led a reliability improvement initiative for the FGD NE system through fault isolation enhancements. Reduced system trips by 40% and maintenance hours by 30%. Improved operational reliability and environmental compliance.
AWS Cloud Practitioner Essentials
AWS Skill Builder
June 1, 2026 – Present
AWS Artificial Intelligence Practitioner Learning Plan
AWS Skill Builder
June 1, 2026 – Present
Certified Data Analyst
Skillovilla
June 1, 2026 – Present
Certified 5S Internal Auditor
Quality Circle Forum of India (QCFI)
January 1, 2024 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from ML models to serverless pipelines and an AI assistant, shows a broad interest in AI/ML applications. However, their professional experience is primarily in maintenance analysis and operational consulting within industrial environments, which, while data-driven, is not directly aligned with a pure AI Engineer role. The certifications in AWS AI Practitioner and Data Analyst indicate an effort to bridge this gap, but the core professional roles are less directly relevant to advanced AI/ML development. The target role of 'AI Engineer' requires a deeper focus on AI/ML specific projects and contributions beyond data analysis and ETL.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving abilities, a commitment to continuous learning in AI/ML, and experience in collaborating with cross-functional teams. Their background in operational analytics and process improvement suggests a practical, results-oriented approach. The experience in identifying process gaps and recommending KPI-based monitoring frameworks indicates a strategic mindset for operational excellence.