Results-driven Data Analyst with SYMET LABS PVT. LTD., proficient in SQL and Python. Enhanced decision-making through interactive Power BI dashboards and automated data processes, boosting productivity by 25%. Collaborated with cross-functional teams to identify trends and deliver actionable insights, demonstrating strong analytical and communication skills.
IT Strategy Development & Analysis, Texas Instruments, Created a new IT strategy using Porter's Five Forces and SWOT analysis with an emphasis on client relationships, risk management, and digital transformation. Developed practical skills in data analysis, IT frameworks, and strategic planning, coordinating technology with business objectives. Digital Innovation: SMART Helmet Development, Created a SMART helmet prototype that incorporates Internet of Things sensors to improve motorcycle safety by providing real-time hazard notifications. Researched, modeled, and tested the solution for scalability and user uptake as part of a cross-functional team. Heart Disease Prediction (Machine Learning), Using SVM, Random Forest, Logistic Regression, and Naïve Bayes, a predictive model was constructed with an accuracy of >85%. Identified important risk variables through the analysis of healthcare datasets, allowing for the development of early intervention plans. Online Ordering System for Restaurants | Full-Stack Development, Reduced client wait times by 25% by designing and implementing a safe online ordering platform with customizable menus, real-time order tracking, and payment gateway integration (Stripe/PayPal). Used Python (Django/Flask) and SQL to create a backend system for order/payment administration, guaranteeing smooth connection with inventory, CRM, and point-of-sale systems to automate data flow. The average order value increased by 15% as a result of menu layout optimizations made using platform data on customer behavior. Increased protection: 40% fewer fraud incidents occurred as a result of the implementation of encryption and PCI-DSS compliance for secure transactions. Business Process Re-engineering (BPR) Proposal for Tesla Supply Chain | Supply Chain Analytics & Process Optimization, Through data analysis of production reports and market trends, major bottlenecks in Tesla's supply chain (such as shortages of lithium-ion batteries and delays in chips) were identified, resulting in a 20% quicker identification of the underlying causes. Suggested solar-powered car models as a lithium battery substitute, which would lessen reliance on limited sources and, according to simulations, minimize production delays by 30%. Redesigned inventory strategy with a 15% lower chance of stockouts, supported by a cost-benefit analysis that suggests switching from Just-in-Time (JIT) to buffer stock systems. Elon Musk's equation (Output = Facility Volume x Density × Velocity) was used to model production efficiency and prioritize high-impact automation in Fremont Factory operations. Analysis of stakeholder impact: used BPMN to map AS-IS vs. TO-BE processes, showing that fewer supplier dependencies might save more than $2 million annually. Subscription Pricing Optimization Model | Python, Integer Linear Programming (ILP), Using Integer Linear Programming (PuLP in Python), a data-driven pricing model was created to improve digital service subscription prices, resulting in a 22% increase in predicted income. Price-to-value alignment was improved by 30% based on sensitivity analysis using a combination of market data (competitor pricing, customer preferences) to define model parameters. Determined the ideal plan combination (Plans A and C), which reduced customer churn risk by 15% in simulations by striking a balance between premium features and cost. Sensitivity analysis was carried out to measure the effects of price and cost changes, allowing for dynamic pricing strategies for market flexibility.