Data Engineer with less than a year in Big Data Analytics & Machine Learning
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Computer Engineering graduate with PG-Diploma in Big Data Analytics (C-DAC), skilled in Python, SQL, machine learning, and data visualization. Internship experience at JPMorgan Chase working with financial datasets and building real-time analytics dashboards.
KNOW-IT, Centre for Development of Advanced Computing (C-DAC)
P.G - Diploma · Big Data Analytics
February 1, 2025 – August 1, 2025
Ajeenkya D.Y Patil School of Engineering
Bachelor of Engineering · Computer Science
January 1, 2020 – August 1, 2024
JPMorgan Chase
Software Engineering Job Simulation
July 1, 2023 – August 1, 2023
Pune, Maharashtra, India
Earthquake Prediction
June 1, 2026 – Present
Analyzed seismic records dataset using PySpark and Hadoop, uncovering key data patterns that drove a 15% reduction in model training time and a 3% improvement in predictive accuracy, enabling geospatial risk analysis. Engineered and preprocessed structured datasets using SQL, performing comprehensive exploratory data analysis (EDA) to identify feature correlations and eliminate data quality issues prior to model training Built an interactive Streamlit web application to present real-time earthquake predictions, enabling non-technical stakeholders to explore model outputs without requiring direct data access. Designed Tableau dashboards to communicate data-driven insights to stakeholders, consolidating multi-source seismic metrics into a single visual reporting interface.
View ProjectCredit Risk Analysis
June 1, 2026 – Present
Developed a credit risk prediction system using 30,000+ customer records and 20+ features, achieving 85% accuracy in identifying potential defaulters. Executed data cleaning and exploratory analysis by handling 12% missing values and detecting outliers, improving model efficiency by 10%. Trained multiple classification algorithms including Logistic Regression and Random Forest, boosting ROC-AUC from 0.75 to 0.83 through hyperparameter tuning. Applied feature engineering and class balancing techniques, increasing minority class recall by 15% for better high-risk customer detection.
View ProjectJ.P. Morgan's Software Engineering on Forage.
Forage
June 1, 2026 – Present
Microsoft Certified: Azure Data Fundamentals
Microsoft
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects cover diverse domains like earthquake prediction and credit risk analysis, showcasing adaptability. The JPMorgan Chase simulation aligns well with industry practices. The pursuit of a PG-Diploma in Big Data Analytics and certifications like Azure Data Fundamentals indicates a commitment to continuous learning and staying current with relevant technologies, which is a positive cultural fit indicator. The target role of Data Engineer aligns with the candidate's demonstrated skills in data processing, ETL, and data visualization.
Soft Skills & Operational Fit
The candidate demonstrates a proactive learning attitude through academic projects and certifications. The JPMorgan Chase simulation indicates an ability to work on real-world tasks and resolve technical issues. Project descriptions suggest an understanding of stakeholder communication through data visualization. However, without specific psychometric test results, a detailed assessment of logical reasoning, stress handling, and team collaboration is not possible.