Rajasvi Vinayak Sharma

Rajasvi Vinayak Sharma has a diverse work experience in the field of data science and machine learning.

- From 2016 to 2017, they worked as a Summer Research Intern at the Indian Institute of Space Science and Technology, where they studied ML theory and implemented algorithms such as Random Forest and AdaBoost. Rajasvi Vinayak also conducted research on the comparison between Traditional and Ensemble ML methods.

- In 2017, they served as a Machine Learning Intern at Samsung R&D Institute, Noida, where they contributed to the Bixby AI Team.

- From 2018 to 2021, Rajasvi worked at Goldman Sachs as a Data Scientist and Analyst. In the Search Engineering Team, they helped develop a real-time Big Data pipeline for processing internal e-communications. In the Business Intelligence Team, they built models for transforming trade-level data and created visualization layers to track trades and identify operational inefficiencies.

- In 2022, they were a Data Scientist Intern at NVIDIA, where they developed a Time-series Anomaly Detection tool and improved A/B test analysis using causal inference ML models. Rajasvi Vinayak also built user engagement metrics using regression analysis and game completion modeling.

- Currently, Rajasvi is employed at Signos as a Machine Learning Engineer, starting in 2023.

Rajasvi Vinayak Sharma has a diverse education history. They obtained a Master of Science (MS) in Electrical & Computer Engineering with a specialization in Machine Learning & Data Science from UC San Diego between 2021 and 2023. Prior to that, Rajasvi completed a Bachelor of Technology (BTech) in Electronics Engineering from the Indian Institute of Technology (Banaras Hindu University) in Varanasi from 2014 to 2018.

Furthermore, Rajasvi received a Senior School Certification from Lawrence and Mayo Public School, where they studied Maths, Physics, Chemistry, and English from 2012 to 2014.

In addition to their academic degrees, Rajasvi has also acquired several certifications. They completed a Crash Course in Causality: Inferring Causal Effects from Observational Data from Coursera in August 2022. Prior to that, Rajasvi obtained certifications in various topics such as Deep Learning, TensorFlow Development, Neural Networks, Deep Learning Optimization, Sequence Models, Applied Machine Learning in Python, Applied Text Mining in Python, and Introduction to Data Science in Python. These certifications were obtained from Coursera between 2019 and 2021.