Aspiring Data Science & Analytics professional with hands-on experience in Python, SQL, Power BI, and Machine Learning. Skilled in Exploratory Data Analysis (EDA), predictive modelling, and building interactive BI dashboards using DAX and Tableau. Based in Mumbai, I'm currently pursuing my B.E. in Computer Engineering and actively seeking an entry-level Data Science or Data Analytics role to deliver data-driven business insights and solve real-world problems.

• 🎯 Core Focus: Data Analytics, Exploratory Data Analysis, Predictive Modelling, BI Dashboards
• 🧠 Currently Exploring: Machine learning applications in fintech, aviation, and enterprise analytics
• 🌐 Approach: Building practical, real-world datasets and dashboards that mirror actual business problems
• 🔧 Goal: Turning raw data into insights that drive better business decisions

I approach data problems the way a business analyst would: start with the question that matters to a stakeholder, then work backward to the datasets, transformations, and visuals that answer it. My project portfolio spans fintech, aviation, fundraising, and telecom, and consistently focuses on measurable outcomes — cutting manual reporting time, catching fraud earlier, or flagging churn risk before it happens.

I'm comfortable owning the full analytics lifecycle: designing schemas in SQL, cleaning and engineering features in Python, validating findings with statistical methods, and packaging results into Power BI / Tableau dashboards that non-technical stakeholders can act on. I'm now looking to bring that same rigor to an entry-level Data Science or Data Analytics team.

Adept at designing enterprise-style datasets and analytics solutions across fintech, aviation, and retail.

• ShopVerse FinTech Analytics Solution (Python, SQL, Power BI, DAX) Built a FinTech analytics solution to monitor online payment transactions, detect fraudulent activity, and analyze customer behavior. Automated transaction reporting with an interactive Power BI dashboard — cutting manual analysis time by 70% (10 hrs/week → 3 hrs) and improving real-time fraud detection.

• Fundraising Business Intelligence Dashboard (Python, SQL, Power BI, Tableau, DAX) Designed a BI solution to analyze fundraising campaigns and track donor contributions. Integrated multi-source data via SQL and built KPI dashboards in Power BI, reducing manual reporting effort by 60% and improving campaign visibility.

• Client Dataset Analysis & Insights Dashboard (Python, SQL, Power BI, Tableau, DAX) Partnered with a client to clean and analyze their raw operational dataset, uncover key trends, and deliver a self-service reporting solution — cutting manual reporting time by over 50%.

• NexusPay Transaction Database (SQL, Database Design) Designed a scalable database architecture for a fast-growing fintech platform supporting P2P transfers, merchant payments, virtual cards, and micro-investments.

• Aerox NextGen Database (Power BI) Built an aviation analytics solution to monitor flight operations, passenger booking behavior, revenue performance, aircraft utilization, and crew management.

• Heart Disease Prediction Model (Python, Scikit-Learn) ML pipeline predicting heart disease risk from clinical and wearable-device data using a Random Forest classifier with SMOTE, plus CI via GitHub Actions.

• Supply Chain Prediction Model (Python, Scikit-Learn) ML regression pipeline predicting warehouse product weight from supply chain operations data using Random Forest.

• Telecom Churn Prediction Model (Python, Scikit-Learn) Classification model that analyzes customer data to predict churn, helping identify at-risk customers for proactive retention.

Programming & Databases

Machine Learning

Deep Learning

MLOps

Data Analysis & Visualization

Tools & Platforms

Data Analysis

Excel Skills

Machine Learning Techniques

Core Concepts

📫 Let's connect — open to entry-level Data Science / Analytics opportunities and conversations about data and insights.