- Developing daily, weekly, and monthly Operational reports and dashboards utilizing Excel, PowerPoint, and Salesforce to analyze business requirements and resource allocation to streamline the overall project of Asylum Seekers for NY City Hall.- Implemented and managed a small team to automate weekly reports through QuickBase that increased reporting efficiency by 50% while reducing the required time by 30% resulting in streamlined report deliveries to the Stakeholders.- Managing, and scripting Databases such as JotForm, Airtable, and MySQL to fetch data to perform analysis and comparative visualization through Excel and Figma.- Leading a small team to establish end-to-end integration between two Salesforce systems to enhance data synchronization and operational efficiency.- Performing data audits to validate data accuracy, and logic workflows and to capture outliers.

- Designed user-friendly dashboards using Figma and plugins to automate dashboard creation.- Developed and maintained documentation such as Data Dictionary, Standard Operating Procedure, Statement of Work, Mockups, and Integration logs to provide detailed information internally and to the stakeholders.- Cultivated cross-team collaboration to ensure development plans are strategically aligned with business objectives, driving project success and optimizing resource utilization.- Developed workflow designs using Lucidchart to streamline processes, enhance clarity, and support effective decision-making across teams

- Developed enterprise-level Python web applications using Flask to perform material analysis based on their properties.- Implemented Machine learning and Deep learning models like Regression, and Neural Networks, via Python to predict material optical, mechanical, electrical, and physical properties, with segmentation and tuning improving the accuracy of the result by 70% and speed efficiency by 50%.- Managed, established, tested, and maintained database connections and scripting MySQL to fetch and validate data from Excel and CSV files for material analysis and comparative visualization using Matplotlib and Seaborn.- Designed and deployed user-friendly interactive dashboards in Tableau, enhancing data visualization and user experience- Coordinated Agile workflow using Slack, overseeing design reviews, code reviews, and daily stand-ups with the QA team to ensure project quality and timely delivery.

- Led the development and implementation of Python-based automated solutions to monitor student performance to track attendance and grades across multiple science streams.- Directed cross-departmental collaborations to provide actionable insights and trend analysis in lab projects to stakeholders.- Delivered interactive Tableau dashboards, effectively presenting complex data trends and correlations to senior leadership.- Developed standardized analysis methodologies and data integrity protocols, to ensure informed strategic decision-making.- Defined project requirements, created detailed use cases, and managed testing and validation processes, resulting in comprehensive system design documentation with actionable recommendations.

Teaching Physics & Data Science experiments to undergraduate students - demonstration,management of entire class, grading and problem solving.

- Directed a small team in the development of a Python-based machine learning application, leveraging object-oriented programming to analyze neutron monitor data for space weather monitoring and prediction.- Coordinated the deployment and continuous improvement of machine learning models, using GitHub for version control to ensure seamless error management and integration of new training data, improving prediction metrics.- Co-authored a research white paper on applying machine learning clustering techniques, such as K-means, to satellite data, effectively identifying and detecting energetic particles, contributing to advancements in space weather prediction.

- Deployed Python application with HTML, and CSS, to detect and analyze solar magnetic field lines from scientific images.- Conducted data transformation and data cleaning for statistical and computational modeling through Scikit-learn with SciPy for calculating accurate properties providing improvement with continuous development and integration with JSON.- Performed data visualization to demonstrate the result of predictive modeling through Matplotlib and Plotly.- Published documentation of operational issues, and code reviews with detailed solutions and recommendations to the stakeholders.- Incorporated Agile methodologies for reporting and presenting improvements to the technical lead to adapt new findings.