Data Science with less than a year in Python, ML, and Data Analysis
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Assessing your cultural and operational fit
Results-driven Data Analyst and aspiring Data Scientist with a strong foundation in Python, machine learning, and statistical analysis, currently advancing expertise through an MCA program. Demonstrated ability to build end-to-end ML pipelines, conduct in-depth exploratory data analysis, and deliver data-driven insights through compelling visualizations. Adept at working with structured datasets using MySQL and Python, with a keen interest in solving real-world problems through data. Seeking a challenging role where analytical skills and technical knowledge can drive measurable business impact.
Khwaja Moinuddin Chishti Language University, Lucknow
Master of Computer Applications (MCA)
August 1, 2024 – June 30, 2026
Khwaja Moinuddin Chishti Language University, Lucknow
Bachelor of Computer Applications (BCA)
August 1, 2021 – June 30, 2024
U.P. Board
Intermediate (12th)
N/A – May 31, 2021
U.P. Board
High School (10th)
N/A – May 31, 2019
Student Performance Prediction System
June 24, 2026 – Present
Engineered an end-to-end ML pipeline to predict student academic outcomes using behavioural and demographic data, achieving 87% classification accuracy with a Random Forest model. Conducted thorough data pre-processing including null handling, label encoding, and feature selection to improve model reliability and reduce dimensionality by 30%. Designed and managed a normalized MySQL database schema for structured dataset storage; automated data retrieval using Python (PyMySQL). Developed Matplotlib dashboards to visualize performance trends, confusion matrices, and feature importance, making findings accessible to non-technical stakeholders.
Stock Market Prediction & Analysis System
June 24, 2026 – Present
Collected, cleaned, and processed 5+ years of historical stock data for 10 companies using Python and Pandas, ensuring data integrity for time-series modelling. Performed comprehensive EDA uncovering key volatility patterns, moving averages, and cross-stock correlations, providing actionable trading signals. Implemented and compared multiple ML models (Linear Regression, LSTM-inspired sequential logic) to forecast closing prices with a mean absolute error below 3%. Produced interactive multi-panel visualizations with Matplotlib to communicate market trends and model performance in a clear, stakeholder-ready format.
Cultural Fit Analysis
The candidate's personal projects demonstrate initiative and a passion for data science, aligning with a culture that values self-starters and continuous learning. The pursuit of an MCA degree while actively working on projects shows dedication. The projects cover different domains (student performance, stock market), indicating versatility. However, the lack of professional experience or team-based projects makes it difficult to fully assess cultural fit in a collaborative work environment.
Soft Skills & Operational Fit
The candidate's resume highlights 'Analytical Thinking', 'Problem Solving', 'Team Collaboration', and 'Communication' as soft skills. Project descriptions demonstrate problem-solving through data analysis and communication through visualization. However, without direct assessment or interview data, the depth of these skills and their operational fit in a team environment cannot be fully validated.