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AI Engineer with less than a year in Data Science & Software Engineering
Detail-oriented Data Analyst, Data Scientist, and Software Developer with strong expertise in Python, SQL, Machine Learning, and fundamentals of full software development. I am skilled in data analysis, statistical modeling, machine learning algorithms, scalable software design, and backend development. Experienced in building data-driven applications, implementing ML models, designing ETL pipelines, and developing analytical dashboards. Strong foundation in Data Structures & Algorithms (DSA), Object-Oriented Programming (OOP), database management (MySQL, MongoDB), exception handling, and clean code practices. I am passionate about solving real-world problems using data science and software engineering.
JSPM University
Masters of Technology · Computer Science & Engineering
August 1, 2023 – June 30, 2025
JSPM's Imperial college of engineering & research
Bachelor of Engineering · Computer Engineering
August 1, 2018 – June 30, 2022
Flourisense Technologies LLP
Data Science, AI/ML Developer Intern
July 1, 2025 – January 1, 2026
Pune, Maharashtra, India
ML Salary Predictor Web Application
June 17, 2026 – Present
• Built an end-to-end ML-powered web application using Flask and Python to predict salaries with 91% R2 score, utilizing Random Forest Regressor trained on 5,000+ data points across experience, education, and role variables. • Implemented a complete ETL pipeline processing 5,000+ records - including data cleaning, feature engineering, and label encoding - reducing preprocessing time by 60% compared to manual methods. • Designed a REST API endpoint (/api/predict) using Flask serving 100+ JSON-based ML predictions per session, enabling seamless integration with external applications. • Integrated MySQL database with full CRUD operations to store and manage 5,000+ prediction history records using optimized SQL queries. • Achieved MAE of $3,200 and cross-validation score of 0.89, demonstrating model robustness across unseen data.
View ProjectData Analytics Projects
June 17, 2026 – Present
• Delivered 6+ end-to-end analytics solutions using Python, SQL, and Power BI - covering data ingestion, EDA, feature engineering, and visualization across diverse business domains. • Automated 4+ reporting pipelines using Python scripts, reducing manual reporting workload by 70% and improving operational efficiency. • Applied statistical analysis with Pandas, NumPy, Matplotlib, and Seaborn to identify patterns and anomalies across datasets of 20,000+ rows.
View ProjectPower BI Business Intelligence Dashboards
June 17, 2026 – Present
• Developed 5+ interactive Power BI dashboards transforming 5 complex datasets into executive-level visual reports using DAX measures, Power Query transformations, and custom data models. • Automated SQL-to-Power BI data pipelines, eliminating 6+ hours of manual weekly reporting and improving data freshness from weekly to real-time. • Implemented data cleaning and normalization reducing data inconsistencies by 45%, ensuring accuracy across all dashboard metrics.
View ProjectUtilizing multi-view chest x-ray 3D reconstruction to improve Thorax Disease Diagnosis
IEJRD
May 1, 2025 – Present
Real time identity identification using Deep Learning
IEEE
May 1, 2022 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from ML web applications to data analytics and deep learning research, indicates a broad interest in the AI/ML domain. Their academic background (Master's in Computer Science & Engineering) and internship align well with an AI Engineer role. The involvement in research and publications suggests a proactive and learning-oriented individual, which is a positive cultural fit for innovation-driven environments. However, the experience level is still nascent, primarily consisting of an internship and personal projects, which might require more mentorship in a senior role.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through their LeetCode achievements and project work. Their ability to automate reporting and ETL pipelines suggests an efficiency-oriented mindset. The project descriptions indicate a detail-oriented approach to data analysis and model evaluation. While direct evidence of teamwork or stress handling is limited, the successful completion of complex projects and research papers implies a degree of self-management and perseverance.