Welcome to my GitHub repository! This repository serves as a showcase of my work, skills, and interests. Below, you'll find more information about me and my experience.
Highly motivated, technologically inquisitive Data enthusiast with over 6 years’ experience in solving business problems using data and analytics. Proficient in using statistics, machine learning techniques, programming & database methods for problem solving. Proven history of successfully working on solo and group projects. My contributions at the Neuroscience Department in UT Dallas as a student assistant led to me being honored with the ‘Student Employee of the Year Award’ for 2023-2024, reflecting the impact of my work in enhancing processes and achieving notable results.
- 🔭 I’m currently working on building chatbots with integration of the gpt-3.5-turbo.
- 🌱 I’m currently learning the concepts of Large Language Models (Generative Pre-trained Transformer)
- 👯 I’m looking to collaborate on leveraging generative AI techniques within the healthcare and finance sectors
- 💬 Ask me about Data Anaytics, Visualization, ML, DS tools..
- ⚡ Fun fact: I love exploring new places and camping under the stars! 🏕️✨
MS Business Analytics, The University of Texas at Dallas, 2024
Bachelor of Engg - Electronics & Communication, Jawaharlal Nehru Technological University
Data Scientist, The University of Texas at Dallas (May 2023 - Current)
In my role, I've been responsible for designing, developing, and maintaining visually engaging and interactive single-cell RNA web application dashboards using RShiny. These dashboards have allowed users to effectively interact with large and complex datasets, enhancing their data analysis capabilities. Additionally, I led the development and deployment of a centralized Sensoryomics web application, streamlining access to diverse datasets and implementing Git version control for efficient collaboration and management. Furthermore, I developed a comprehensive Power BI dashboard for internal budgets, empowering stakeholders to allocate grants efficiently and monitor expenditure. This initiative resulted in a notable 25% reduction in administrative time and significantly improved financial decision-making capabilities within the organization.
Data Scientist II , Honeywell (June 2021 - July 2022)
I collaborated with cross-functional teams to gather requirements and design business requirement documents, implementing data-driven solutions that delivered valuable insights to leadership teams and integrated results into operational platforms. Utilizing the random forest algorithm in R, I developed a resource acquisition model resulting in a 30% reduction in hiring time and accurately forecasted terminations and vacancies for upcoming quarters with 70% accuracy. Additionally, I independently designed and implemented the Compensation Offer Tool, a statistical algorithm providing managers and hiring teams with valuable insights for talent acquisition and internal job changes through an RShiny dashboard user interface. Moreover, I developed KPI metrics to evaluate program effectiveness using descriptive statistics and automated the end-to-end process using Alteryx ETL tool and R programming, resulting in saving nearly 400 hours annually. In addition, I have used Alteryx tool for predictive and reporting analytics.
Data Scientist I , Honeywell (Aug 2019 - May 2021)
I spearheaded efforts to streamline processes, saving nearly 600 hours annually through automation using R and the Alteryx tool. Additionally, I collaborated on building a real-time predictive model for employee churn prediction, resulting in significant cost savings of almost $10 million annually by enabling HR and leadership teams to prevent turnover through actionable insights. Moreover, I played a pivotal role in the migration of data from local SSMS to Hadoop in the Domino system and facilitated the migration of projects to the cloud. I also took charge of designing and presenting communication analytics dashboards to executive teams using Tableau, offering insights crucial for informed decision-making. Furthermore, I leveraged Python to implement NLP models for sentiment analysis and topic extraction on communications and survey data. Lastly, I contributed to the development of technical documentation for tools and SOPs for projects and provided training to over 5 new team members, proactively delivering accurate data analysis results to business leaders and customers, thereby enhancing decision-making processes.
Programer Analyst, Cognizant (Mar 2018 - August 2019)
I developed and implemented a smart auditing process using machine learning techniques across various marketing regions, leading to a notable 15% increase in transaction error capture and saving 3.7 FTE. Additionally, I enhanced the invoice processing methodology by optimizing transaction delivery through a prioritization algorithm, resulting in a 10% improvement. Furthermore, I designed and implemented operational and ad-hoc reporting dashboards utilizing R Shiny, Power BI, and Excel to track audit and invoice processes efficiently. Moreover, I collaborated closely with internal stakeholders to develop and maintain automation solutions using R, which significantly improved the efficiency and accuracy of analytical reports, contributing to enhanced operational performance.
Feel free to reach out to me via:
- 🌐 LinkedIn: https://www.linkedin.com/in/hemanth-mydugolam/
- 🔗 Portfolio: https://hemanth-mydugolam.shinyapps.io/Portfolio/