Rohit Gurjar

Analytics professional with 3 years of industry experience in the EV automotive and technology domains. Recipient of Dean's Excellence Scholarship Award 2018-19 for top academic performance. Contributed to software development and DevOps infrastructure at Lucid Motors for the launch of '2023 World Luxury Car' awardee Lucid Air. Leveraged advanced analytics at Intel to transform workforce data into actionable insights as part of Workforce Analytics team.

Intel Corporation | Bengaluru, Karnataka | Mar 2024 - Apr 2025

• Analyzed performance ratings using SQL and Python, identifying key trends that improved employee metrics by 10%
• Conducted data-driven turnover analysis that reduced employee attrition by 15% within six months.
• Created and maintained Power BI dashboards for retention monitoring, contributing to a 12%improvement in retention rates.
• Analyzed employee engagement survey data using Python, delivering recommendations that boosted satisfaction by 20%.
• Partnered with cross-functional teams to develop SQL and Power BI reports that enhanced HR decision-making processes.

• Integrated diverse data sources for the Global DevOps team at Lucid, supporting the award-winning Lucid Air electric vehicle platform.
• Developed CI/CD pipelines using Jenkins, reducing processing times by 40% and enabling seamless OTA updates to 10,000+ vehicles globally.
• Orchestrated vehicle data in AWS Redshift and implemented Python ETL processes, improving operational efficiency by 50%.
• Designed MySQL database schema for vehicle configuration data, optimizing stored procedures that reduced load times by 35% across 20+ applications.
• Created Tableau dashboards for fleet monitoring and KPIs, reducing maintenance downtime by 30%.

Master of Science in Business Analytics The University of Texas at Dallas | Richardson, Texas, USA | 08/2018 - 05/2020

Relevant Coursework: High Performance Analytics with SAP, Big Data, Applied Machine Learning, Database Foundations for Business Analytics, Business Data Warehousing, Applied Econometrics and Time Series Analysis.