1)Conducted analysis and computed Greeks for a comprehensive 4-year option dataset, providing key insights into market trendsand supporting effective risk management strategies.2)Automated data retrieval from Dropbox using Selenium, enhancing efficiency and streamlining processes for seamlessinformation access.3)Developed and maintained a comprehensive database of Bhavcopy, covering futures, options, cash, and currency data from 2016to 2023, including lot sizes for accurate representation.4)Implemented a robust validation framework, conducting daily validation checks to ensure data accuracy. Proactively identifiedand addressed issues, promptly alerting the team to maintain the integrity of financial datasets.5)Expertly managed corporate actions and roll adjustments for historical data, enhancing the reliability of information. Played a keyrole in streamlining processes and contributing to data-driven decision-making within the organization.6)Managed the compilation and processing of terabytes of market data from various vendors, ensuring timely delivery to enablefour quant research teams to meet project deadlines.7)Programmed automated jobs to receive raw data from 10+ vendors and reformat them for intraday/ETF trading, options trading,and trading analyses across global geographies (India/US/Japan).8)Developed 10+ data pipelines using Airflow to automate data capture from multiple sources, significantly reducing manual dataingestion workload by 80%.

1)Streamlined US book operations, achieving a 90% reduction in processing time.2)Ensured watertight processes for order management, contributing to day-to-day operational efficiency.3)Conducted financial analysis, generating drawdown sharp ratios and rolling returns for diverse strategies, supporting informeddecision-making.4)Automated daily, monthly, and yearly performance reports for the overall trading book using Python scripting, reducing manualeffort by 70%.

• Developed a tool to target the students to offer the availablecourses.1. Developed a prediction model that predicts which studentis most likely to take a particular course.2. Analysis was done in terms of student profile - Age, Curriculum, College, Interest, Searches, etc.3. Technologies - Data Science and Machine Learning techniques for the prediction models• Took complete handover of the machine learning modulesrequired for a client’s project – ‘A Canteen Application’.1. Analysed trends in app purchases based on historical logdata.2. Developed a recommendation system based on frequentcombinations of food items.3. Recommendation system was built using Apriori algorithmand Collaborative filtering.4. Technologies – Python, MySQL, Machine Learning (Tensor flow, Keras), Web Development (Html, CSS, JavaScript,Php).

-Implemented UI of the company's app in the most optimized manner.-Features such as live chat, Sending and receiving the invitation, notification section, charity section, home screen which includes sharing of posts, stories, etc. were implemented in the app.-Technologies used were Java, Kotlin, UI, MVVM and GraphQL.

Developed the institute’s official android application using optimization technologies like MVVM model and retrofit for API integration. User Interface was developed considering UI-UX standards.