Data Analytics with less than a year in Python, SQL, and BI tools
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Highly motivated and detail-oriented Computer Science Engineering student with solid foundational knowledge in programming and a strong interest in Al and software development. Completed detail-oriented Data Analytics course with projects experience in SQL, Python, Tableau, and leading BI tools. Passionate about transforming raw data into actionable insights to support data-driven business decisions. Eager to contribute analytical skills and project experience in a dynamic and growth-oriented organization.
Jaya Prakash Narayan College Of Engineering
B.Tech · Computer Science Engineering
August 1, 2021 – June 30, 2025
TMRJC, Wanaparthy
Intermediate (MPC) · Education
June 1, 2019 – May 31, 2021
ROBUST INTELLIGENCE OF MALWARE DETECTION USING DEEP LEARING [Academic Major Project]
June 1, 2024 – June 1, 2026
Built a deep learning-based malware detection system using CNN/LSTM models to classify malicious and benign files, including feature extraction from binary data and API call sequences. Designed the system to detect zero-day malware by learning hidden behavioral patterns and achieved high performance using accuracy, precision, recall, and F1-score metrics. Implemented the solution using Python, TensorFlow/Keras, and Scikit-learn with optimized model performance through tuning and validation.
Blinkit Sales & Delivery Analytics Dashboard
June 1, 2024 – June 1, 2026
Analyzed 50,000+ transactional records of a quick-commerce platform to identify top-performing product categories and peak delivery time slots. Built an interactive Power BI dashboard showcasing KPIs: order volume, average delivery time, customer retention rate, and revenue by city. Used Python (Pandas, Seaborn) for data cleaning, outlier removal, and exploratory data analysis (EDA) to uncover hidden patterns. Applied SQL queries to extract customer cohorts and segment them based on purchase frequency and basket size. Identified a 23% revenue concentration in the snacks & beverages segment, leading to a recommendation for targeted promotional campaigns.
Part-Time Job Application & Quick Service Finder [Academic Mini Project]
June 1, 2024 – June 1, 2026
Developed a part-time job application and quick service finder platform enabling users to discover nearby jobs and on-demand services efficiently. Designed features like job search, service listings, user profiles, and real-time matching to connect job seekers with employers/service providers. Implemented the system using modern web technologies with a focus on user-friendly interface, fast search functionality, and scalable architecture
HR Analytics - Employee Attrition Prediction & Insights
June 1, 2024 – June 1, 2026
Conducted end-to-end analysis of an HR dataset (IBM HR Analytics) with 1,470 employee records to understand attrition trends. Performed feature engineering and correlation analysis using NumPy and Pandas to identify top attrition drivers: overtime, job satisfaction, and monthly income. Designed an interactive Tableau dashboard with filters by department, gender, education, and job role for HR stakeholder reporting. Created Excel pivot reports and conditional formatting sheets for quick summary views shared with nontechnical audiences. Derived insight that employees with overtime work had 2.4× higher attrition rate, enabling HR to redesign workload policies.
Exploratory Data Analysis with Python
IBM Developer Skills Network
January 1, 2026 – Present
SQL and Relational Database 101
IBM Developer Skills Network
January 1, 2026 – Present
Python for Data Science
IBM Developer Skills Network
January 1, 2026 – Present
GenAI Powered Data Analytics Job Simulation
TATA (Forage)
January 1, 2025 – Present
Technology Job Simulation
Deloitte
January 1, 2025 – Present
Python Programming
JILT (JILT Engineering Consultants)
January 1, 2022 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong alignment with the target role of Data Analytics, covering various aspects from sales and HR analytics to deep learning for malware detection. The diversity in project domains (e-commerce, HR, cybersecurity) and the use of a broad range of tools (Python, SQL, Power BI, Tableau, TensorFlow/Keras) suggest adaptability and a willingness to explore different challenges. The certifications further reinforce a proactive learning attitude, which is a positive indicator for cultural fit in a growth-oriented organization.
Soft Skills & Operational Fit
The candidate highlights analytical thinking, problem-solving, data storytelling, attention to detail, team collaboration, and communication as soft skills. These are crucial for a Data Analytics role, indicating a good operational fit for data-driven environments. The project descriptions also reflect these skills in practice, such as identifying revenue concentration and attrition drivers.