Ajinkya G
About Ajinkya G
Ajinkya G is a Machine Learning Engineer at Carta, specializing in statistical modeling and data visualization. He has a strong background in data science and business analytics, with experience in MLOps practices and SQL.
Work at Carta
Ajinkya G has been employed at Carta as a Machine Learning Engineer since 2021. In this role, he focuses on the development of machine learning models aimed at optimizing financial processes. His work contributes to enhancing data-driven decision-making within the organization. Ajinkya applies his advanced skills in statistical modeling and data visualization to improve the efficiency of these models, ensuring they meet the needs of the business.
Previous Experience at Discover Financial Services
Prior to his current position at Carta, Ajinkya G worked as a Data Scientist at Discover Financial Services from 2017 to 2021. During his four years in this role, he developed expertise in data analysis and model development. His experience at Discover helped him build a strong foundation in data science, which he later applied in his role at Carta.
Education and Expertise
Ajinkya G holds a Master’s Degree in Business Analytics from the University of Illinois Chicago. He also earned a Bachelor of Engineering in Computer Science from Pune Institute of Computer Technology. His educational background provides him with a strong foundation in both technical and business analytics, allowing him to effectively combine data science skills with business acumen.
Technical Skills and MLOps Experience
Ajinkya G possesses advanced skills in statistical modeling, data visualization, and SQL. He is experienced in implementing MLOps practices, which streamline machine learning workflows and enhance model deployment efficiency. His programming expertise allows him to manage and analyze large datasets effectively, supporting data-driven decision-making processes.
Contributions to Machine Learning Development
At Carta, Ajinkya G has contributed to the development of machine learning models that optimize financial processes. His work focuses on improving the efficiency and effectiveness of these models, which play a crucial role in the company's operations. His contributions reflect his commitment to leveraging machine learning for business improvement.