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Data Science with 2+ years in Data Analysis & Machine Learning
Results-driven entry-level Data Analyst and recent Computer Science & Design graduate with hands-on internship experience in SQL, Python, Power BI, and Excel. Proven ability to collect, organize, clean, and interpret large datasets to identify trends, patterns, and actionable business insights that drive informed decision-making. Built end-to-end machine learning projects for energy consumption forecasting and used-car price prediction; designed interactive Power BI dashboards for business KPI tracking. Adept at creating reports, dashboards, and visualizations for management and stakeholders. Strong problem-solving, analytical thinking, and attention to detail combined with clear communication skills and a track record of improving operational efficiency and business performance through data-driven solutions.
Vimal Jyothi Engineering College, Kannur University
Bachelor of Technology · Computer Science and Design
August 1, 2021 – June 30, 2025
Spinnaker Analytics
Data Analyst Intern
February 1, 2026 – April 1, 2026
Bengaluru, Karnataka, India
Boston Institute of Analytics
Data Analyst Trainee
July 1, 2025 – January 1, 2026
Bengaluru, Karnataka, India
Rever Tech Solutions
Python & Machine Learning Intern
July 1, 2024 – Present
Cochin, Kerala, India
E-Commerce Customer Segmentation & Churn Prediction
January 1, 2026 – January 1, 2026
Collected and organized 50,000+ customer records; applied RFM scoring and K-Means clustering to identify 4 revenue-ranked segments findings structured as a marketing brief recommending budget reallocation toward the top-20% high-value cohort to improve business performance. Built churn prediction model (Logistic Regression + Random Forest); achieved F1-score of 0.83, outperforming baseline by 14%; identified top-5 churn drivers to support retention strategy and informed decision-making. Presented segment insights and churn risk matrix to a business panel of 5 reviewers; interpreted data patterns into plain-language retention recommendations, demonstrating data storytelling and stakeholder communication skills.
View ProjectBlinkit Grocery Sales & KPI Dashboard
December 1, 2025 – December 1, 2025
Wrote SQL queries with CTEs to compute 4 business KPIs (Total Sales, Average Sales, Item Count, Average Rating) across Tier 1/2/3 outlet locations; cross-validated outputs in Excel Pivot Tables zero discrepancy across all tiers, confirming data accuracy. Designed a single-page Power BI dashboard (5 visual types, 3 dynamic slicers) enabling management to self-serve outlet performance data - eliminated ad-hoc query requests from the reporting workflow, improving operational efficiency and business performance visibility.
View ProjectOnline Retail Sales Analysis Trend & Revenue Intelligence
November 1, 2025 – November 1, 2025
Cleaned raw transactional data (filtered nulls, negative quantities, zero-price records) and engineered a Revenue column (Qty x Unit Price), ensuring data accuracy and enabling time-series analysis previously unavailable in the dataset. Identified top-10 revenue products and 3 seasonal demand patterns via monthly trend analysis findings structured as an inventory planning recommendation with projected stock optimization impact, supporting informed decision-making.
View ProjectCultural Fit Analysis
The candidate's project diversity across retail, sales, customer, and IoT domains, coupled with internships at different companies, suggests adaptability and a broad interest in applying data science principles to various business challenges. Their proactive approach to identifying business value and improving efficiency through data aligns with a culture that values innovation and impact. The academic projects and internships show a consistent drive to learn and apply new skills, indicating a good fit for a growth-oriented environment.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving, analytical thinking, and attention to detail. Their experience in collaborating with cross-functional teams and presenting findings to non-technical stakeholders indicates good communication and teamwork skills. The focus on improving operational efficiency and business performance through data-driven solutions aligns well with a results-oriented work environment.