• Automated restaurant menu extraction from Uber Eats using Python + Playwright, reducing manual entry time by 95%.

• Designed workflow to scrape dynamic Doordash menus with Selenium + stealth Playwright, achieving 80%+ item coverage including modifiers and pricing.

• Implemented network interception and API parsing to capture comprehensive restaurant data (categories, items, prices, modifiers, descriptions) from GraphQL endpoints.

• Built end-to-end workflow in n8n, enabling seamless script orchestration and automated database ingestion of structured JSON menus.

• Reduced menu digitization time from several hours to ~60 seconds (UberEats) and ~30 minutes (DoorDash) per restaurant.

• Designed and deployed efficient data pipelines for financial stock forecasting using Python and PySpark, achieving a 75% improvement in data accuracy through optimized preprocessing techniques.

• Integrated and analysed large-scale financial datasets from diverse sources using SQL and Python, ensuring data accuracy and integrity, and conducted advanced statistical analyses to identify patterns and market trends.

• Improved data transformation efficiency by 30% using Min-Max and Standard scaling techniques, enhancing data quality for predictive modelling.

• Developed interactive Tableau dashboards to visualize data insights and key performance indicators (KPIs), enabling stakeholders to access real-time analytics and reducing report generation time by 40%.

• Optimized SQL queries, cutting execution time by 30% and enhancing reporting efficiency for large datasets.

• Leveraged Matplotlib to design data visualization strategies for financial trend analysis, uncovering stock patterns and outliers to enhance predictive modelling and decision-making.

• Utilized PySpark for big data processing, enabling efficient distributed analysis of large-scale financial datasets.

• Redesigned the Python programming curriculum to include hands-on ML projects, leading to a 5% increase in student grades.

• Delivered comprehensive lectures on Python programming, covering fundamental concepts and advanced techniques.

• Encouraged engagement through hands-on exposure to tools like TensorFlow, Pandas, and NumPy.

• Employed Python to analyze data, automate dataset processing, and produce comprehensive reports, reducing manual effort and improving data accuracy.

• Developed a ServiceNow dashboard that improved ticket acknowledgment and resolution by 20% through real-time visibility and automation of service requests.

• Leveraged tools such as Python, SQL, and data management systems to optimize data access and user authentication for SGRE across 50+ countries, enhancing system reliability by 25%.

• Utilizing Agile Scrum and Kanban, improved team productivity by 10%, reduced project delivery times by 20.

• Developed interactive dashboards in Tableau, delivering actionable insights and reducing manual reporting efforts by 40%.