Headline

Data Scientist 2 at Locus | Eugene McDermott Fellow | UT Dallas | Chennai Mathematical Institute

About

As a graduate student in Supply Chain Management at The University of Texas at Dallas, with a strong background in data science and operations research, I am passionate about applying advanced analytics, econometrics, and machine learning to solve real-world challenges in supply chain optimization and decision-making. During my academic journey, I transitioned from a Ph.D. program to focus more deeply on data-driven solutions for operational efficiency. My research and industry experience have equipped me with a unique skill set, allowing me to blend theory and practice. I have worked on projects ranging from school choice modeling to econometric adoption systems and enhancing decision-making processes for farming cooperatives during my time as an Eugene McDermott graduate research fellow. With hands-on experience in machine learning, reinforcement learning, computer vision, and natural language processing, I’ve contributed projects, such as optimizing next-day renewable energy forecasts and implementing advanced NLP frameworks for document classification. My job at Mercedes-Benz R&D, where I analyzed Mercedes Benz and competitor car lines for ergonomic satisfaction, automated detection of ingress-egress using motion capture data with the help of computer vision and used Generative Adversarial Networks to populate accident data for accident prevention has solidified my proficiency in applying AI to drive meaningful business outcomes. I am also committed to leadership and community service, founding Aastha Academy to provide education to underprivileged children and actively engaging in volunteer initiatives. Key Areas of Expertise: Econometric and Mathematical Modeling Machine Learning (Supervised, Unsupervised, Deep Learning) Reinforcement Learning, Computer Vision Optimization, Linear Programming, Time Series Analysis Supply Chain Analytics, Operations Research Leadership in Community and Educational Initiatives I’m always eager to collaborate on projects that push the boundaries of what’s possible in supply chain management, operations research, and data science. Let’s connect if you're interested in discussing how innovative data-driven solutions can drive efficiency and performance in your organization!

Location

Bengaluru

AI stack

anthropic apis

claude code

claude

codex

cursor

Work experience

Data Scientist at GeoIQ, Oct 2026 - Present · 1 mo, Bengaluru, Karnataka, India

Data Scientist at Locus, Sep 2025 - Oct 2026 · 1 y 1 mo, Bengaluru

Eugene McDermott Graduate Research Assistant at The University of Texas at Dallas, Aug 2022 - Jul 2025 · 3 yrs, Dallas, Texas, United States, **School Choice Modeling** - Centralized school admission systems face challenges in balancing fairness and efficiency and I was tasked with creating mathematical bounds to optimize school admissions. - Developed a model to establish upper and lower bounds for centralized school examinations, which would ensure fair and efficient allocation. - Contributing to ongoing research aimed at improving admission policies for better outcomes. **Adoption Matching System** - Existing adoption systems struggle with matching children to adoptive families, leading to delays or mismatches and I was responsible for developing an econometric model to improve the matching process. - Analyzed key variables and created a model to optimize compatibility between children and adoptive families. **Farming Cooperatives** - Farming cooperatives lack real-time data-driven insights for decision-making in accessing micro loans, affecting productivity. - Developed a model to assess the impact of adding data layers to cooperative decision processes.

Automotive Ergonomics Engineer at Mercedes-Benz Research and Development India, Feb 2022 - Jul 2022 · 6 mos, Bengaluru, Karnataka, India, Mercedes Benz aimed to improve ergonomic satisfaction for its carlines compared to competitors. Additionally, accident prevention and process automation were key areas of focus for the company's ongoing projects. I was tasked with analyzing the ergonomics of Mercedes Benz and competitor carlines, automating ingress and egress, and enhancing accident prevention capabilities. I automated the detection of ingress-egress using motion capture data and computer vision. I also employed Generative Adversarial Networks (GANs) to simulate accident data for predictive modeling and prevention. Additionally, I led Reinforcement Learning bootcamps to enhance project innovation. These efforts contributed to improved ergonomic assessments, automated data processing, and the development of advanced accident prevention systems.

Research Intern at Chennai Mathematical Institute, Oct 2021 - Feb 2022 · 5 mos, Chennai, Tamil Nadu, India, I implemented a context-aware approach for counting corn tassels using land cover datasets. Using a deep neural network architecture, I encoded multi-level contextual information into the features it produced. This enabled the network to accurately identify and count corn tassels. The approach significantly improved counting accuracy, providing a solution for large-scale agricultural monitoring and optimizing crop management practices.

Research Intern at Indian Statistical Institute, Kolkata, May 2021 - Feb 2022 · 10 mos, Kolkata, West Bengal, India, Clustering streaming data using decision-theoretic rough sets. Done under the supervision of Prof. Ashish Ghosh, Machine Intelligence Unit Manuscript under works to be submitted to CVPR 2022

Education

Master's degree, Supply Chain Management (Transferred from the PhD program), The University of Texas at Dallas

Master's degree, Data Science, Chennai Mathematical Institute