• Collaborate with Engineering and Product teams throughout the organization and across various entitiesto identify opportunities for solving problems using Data and UX Research.• Propose impactful features and ideas for the in-house Annotation tool by performing UX researchand requirement gathering. - Collaborate with stakeholders to create Technical PRDs that aligned with user needs and product goals. - Conduct revisions to ensure accuracy, and analyzed data to… Show more • Collaborate with Engineering and Product teams throughout the organization and across various entitiesto identify opportunities for solving problems using Data and UX Research.• Propose impactful features and ideas for the in-house Annotation tool by performing UX researchand requirement gathering. - Collaborate with stakeholders to create Technical PRDs that aligned with user needs and product goals. - Conduct revisions to ensure accuracy, and analyzed data to identify areas for improvement.• Propose initiatives for cost reduction and workload automation to improve and optimize the performance.• Perform A/B testing of new productionized features.• Recommend technical solutions for system architectural improvements and design, ensuring feasibilityand efficiency for optimum performance.• Create Dashboards based on SQL/Snowflake queries to make data-driven decisions, monitor data trends,and analyze performance metrics. Show less

• Monitored, analyzed and annotated video data using in-house tool to provide real-time insights and services to the customers, with a 95%+ accuracy, while maintaining the SLA of providing live data within 5 minutes after its generation.• Accumulated ground-truth data by manually labeling and validating the accuracy, to train the ML models and helped achieve 90-96% precision.• Collaborated with R&D and Product teams on multiple features and projects to train ML models for detecting… Show more • Monitored, analyzed and annotated video data using in-house tool to provide real-time insights and services to the customers, with a 95%+ accuracy, while maintaining the SLA of providing live data within 5 minutes after its generation.• Accumulated ground-truth data by manually labeling and validating the accuracy, to train the ML models and helped achieve 90-96% precision.• Collaborated with R&D and Product teams on multiple features and projects to train ML models for detecting various traffic violations, e.g. Seat Belt violation, Tailgating, Cellphone Usage etc., by gathering and annotating video footage, which led to improved driver safety awareness and behavior.• Overall ensured the Data Quality in terms of accuracy, relevancy and consistency. Show less

• Developed scripts using Python/PHP to retrieve and classify Twitter data for Sentiment Analysis, which resulted in a prediction accuracy rate of 90% for the classifier.• Developed scripts to clean, parse, and visualize tweet-content; parsed and segmented tweet-content to create word clouds and frequency tables of words and hashtags associated with customer sentiments towards products.• Scrapped tweets from users' profiles, using Twitter API and extracted JSON responses using the… Show more • Developed scripts using Python/PHP to retrieve and classify Twitter data for Sentiment Analysis, which resulted in a prediction accuracy rate of 90% for the classifier.• Developed scripts to clean, parse, and visualize tweet-content; parsed and segmented tweet-content to create word clouds and frequency tables of words and hashtags associated with customer sentiments towards products.• Scrapped tweets from users' profiles, using Twitter API and extracted JSON responses using the Requests module, to gain insights on users' attitudes towards the company and its products.• Used Plotly to generate insightful visualizations from the structured data, to better analyze patterns and detect trends of customer sentiments towards specific products. Show less