• Ensure end-to-end data pipeline delivery, including submetering devices, data collectors, databases, and reporting applications.• Develop and optimize SQL queries and reports, automating repetitive tasks to enhance efficiency.• Collaborate with the DevOps team to assess improvements, providing support and training for automation and programmatic solutions.• Create and maintain technical and process documentation, ensuring clarity and consistency for stakeholders.

• Reviewing reports to establish baseline customer satisfaction levels.• Monitoring sales figures to identify opportunities for growth in key areas such as seasonal items or new product lines.• Meeting with store associates individually to discuss performance issues or concerns.• Review reports from internal departments to identify areas for improvement or change.• Working with the store manager to develop, implement and monitor policies to ensure compliance with regulations.• Ensuring that the store follows all local, state and federal laws and regulations concerning security, safety and sanitation practices, including food handling procedures.• Assisting customers with inquiries or complaints in person or over the phone, either personally or through the store’s customer service department.• Elevating Front End operations to exceed customer expectations & increase store metrics, resulting in asignificant rise in customer loyalty.• Ensuring store associates are trained in all aspects of their job, including customer service and merchandising standards.• Developing training programs for new hires and existing staff members on topics such as customer service or merchandising standards.

• Collaborated with the back-end team to establish an end-to-end data pipeline on AWS, automating the processing of video content into various formats, i.e. .mp4 to .mov, and enabling widespread content distribution and accessibility across devices.• Setup of a video-on-demand pipeline using S3, AWS Transcribe, and CloudFront• Created a data pipeline that streamlines the ingestion of video content from Vimeo and YouTube and its efficient loading into S3 to be used in the development of models generating high quality speech for video dubbing.

As a Data Analyst during my tenure at GNWebSoft, I played a pivotal role in leveraging data to empower university administrators, optimize resource allocation, and enhance decision-making processes. Through the development of enrollment prediction models, the creation of dynamic Tableau dashboards, and collaborative efforts with cross-functional teams, I contributed to the enhancement of software functionalities and strategic alignment.Key Achievements:- Developed enrollment prediction models by analyzing historical data, enabling university administrators to make informed resource allocation and recruitment decisions.-Collaborated with stakeholders to refine and validate models, resulting in a 10% increase in resource utilization efficiency within the University Management Information System (MIS).-Created interactive dashboards using Tableau, providing real-time insights into financial performance and inventory metrics.-Transformed complex data into user-friendly visualizations that supported data-driven decision-making and empowered stakeholders across departments.-Translated data insights into actionable recommendations, contributing to enhancing software functionalities and features.

I worked on a project at VSPL that included creating a Python-based method for identifying and authenticating human faces. The goal of the project was to improve the security and access management of a commercial building by employing facial recognition technology to verify visitors.My main duties were as follows:-To train and test the machine learning models, a huge collection of facial photos must be gathered and prepared.-Using OpenCV, NumPy, and SciPy libraries to implement machine learning methods for face detection, feature extraction, and verification-Rigorously testing and debugging the solution to make sure it is reliable and accurate-Capturing every step of the process and sharing my results with the teamI gained excellent proficiency in Python programming, machine learning, and computer vision throughout the course of the project. Additionally, I developed my teamwork skills and improved my ability to explain intricate technical ideas to stakeholders who are not technical. I also gained insight into the significance of data privacy and moral issues related to the use of facial recognition technologies.My involvement in the project led to the creation of a very effective and accurate system that could recognise and authenticate human faces in real-time with an accuracy rate of over 95%. The solution was linked into the commercial building's access control system, increasing security and facilitating authorised employee access.