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Data Analyst with 1+ years in Business Intelligence and Machine Learning
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Data Analyst with 14+ months of combined experience in Business Analysis and Data Science, including 9+ months as a Business Analyst in a US-based fintech company and 5 months as a Data Science & Machine Learning Intern. Holds a Master's degree in Computer Applications (MCA) with a strong technical foundation. Proficient in Power BI, SQL, Python, and Excel for EDA, KPI tracking, dashboarding, automated reporting, and predictive analysis. Experienced in transforming large datasets into actionable insights to support data-driven decision-making and business growth.
Farook College, Calicut, University Of Calicut
Bachelor of Computer Science · Computer Science
N/A – June 30, 2021
APJ Abdul Kalam Technological University
Master of Computer Applications · Computer Applications
N/A – June 30, 2024
ZilMoney
BUSINESS ANALYST
August 1, 2025 – Present
US
iDatalytics
DATA SCIENCE AND MACHINE LEARNING INTERN
August 1, 2024 – December 1, 2024
India
ENTRANCE CENTER MANAGEMENT SYSTEM (ECMS)
June 21, 2026 – Present
Developed a comprehensive digital management system (ECMS) to modernize and optimize administrative processes for entrance coaching centers. Centralized enrollment management, attendance tracking, and stakeholder communication across Administration, Students, Teachers, and Parents modules. Designed and implemented the platform using Python, Django, SQLite, and Bootstrap with a modular architecture. Improved operational efficiency, reduced manual errors, and enhanced collaboration through system automation. Delivered a user-friendly and scalable solution supporting seamless end-to-end management workflows. Followed Agile (Scrum) methodology to enable iterative development and continuous improvement.
CUSTOMER CHURN ANALYSIS FULL STACK BI & ML PROJECT
June 21, 2026 – Present
Developed an end-to-end churn analysis and prediction pipeline using SQL Server, Python, and Power BI to identify at-risk customer segments. Built ETL pipelines, data cleaning workflows, and optimized SQL views to ensure high-quality, analysis-ready data. Trained and evaluated a Random Forest classifier using scikit-learn and Pandas, achieving 85%+ recall Created interactive Power BI dashboards to visualize churn trends, revenue impact, and predicted risk segments. Analyzed customer behavior patterns, identifying 2.5x higher churn in month-to-month contracts. Delivered data-driven insights to support targeted retention strategies and improve customer lifetime value.
AI-DRIVEN AUTOMATED LEAD GENERATION PLATFORM
August 1, 2025 – June 1, 2026
Designed and implemented an AI-powered B2B lead intelligence and automated lead generation system using Python, FastAPI, SQL, PostgreSQL, Redis, Dealfront API, and OpenAI GPT-4. Automated lead ingestion, enrichment, intent scoring, and personalized outreach to improve lead qualification and prioritization. Leveraged GPT-4 to generate company summaries, identify key pain points, and create personalized sales outreach emails. Reduced outreach content creation time by ~65% and manual lead research efforts by ~60–70%. Developed intent-based lead scoring models to enable sales and growth teams to focus on high-intent prospects, accelerating lead-to-contact cycles. Built interactive analytics dashboards using React, TypeScript, Material-UI, and Recharts to track lead scores, engagement metrics, outreach performance, and conversion trends. Collaborated with cross-functional stakeholders to translate business requirements into scalable, data-driven, AI-enabled solutions in a US-based fintech environment.
INTERN ATTRITION PREDICTION
August 1, 2024 – December 1, 2024
Developed an end-to-end machine learning solution to predict intern attrition using Python. Performed exploratory data analysis (EDA), data cleaning, and feature engineering to improve data quality and model performance. Trained and evaluated multiple models, including Logistic Regression, Random Forest, and Gradient Boosting. Selected the best-performing model achieving 85% accuracy based on accuracy and error metrics. Optimized model performance using GridSearchCV for hyperparameter tuning. Deployed the final model using Flask, enabling real-time predictions through a user-friendly web interface.
Cloud Computing
IIT Kharagpur
June 1, 2026 – Present
MoEngage Analytics Expert
MoEngage
June 1, 2026 – Present
Google Data Analytics Certificate
June 1, 2026 – Present
Python Fundamentals
Great Learning
June 1, 2026 – Present
Introduction to Internet of Things
IIT Kharagpur
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from academic management systems to professional AI-driven lead generation and intern attrition prediction, shows adaptability and a broad interest in applying data science. Their experience in a US-based fintech company (ZilMoney) and collaboration with cross-functional teams suggests a good fit for a results-oriented, collaborative culture. The certifications in Google Data Analytics and MoEngage Analytics further indicate a proactive approach to continuous learning and alignment with data-centric roles.
Soft Skills & Operational Fit
The candidate demonstrates strong soft skills including communication, team collaboration, and stakeholder management, which are crucial for a Data Analyst role. Their experience in Agile methodologies and working with cross-functional teams indicates good operational fit for dynamic environments. The ability to translate business requirements into data solutions highlights a practical, business-oriented mindset.