About

Kapil Ahuja is a highly skilled Data Scientist and MLOPS Engineer with over 2 years of relevant experience. He is currently working as a Machine Learning Engineer at Chubb, where he is responsible for developing and implementing machine learning models to solve complex business problems. Kapil is well-versed in algorithms and has a strong command of programming languages such as C/C++ and Python. He also has a good understanding of SQL and is involved in data analytics and machine learning. Kapil is a proven team player and problem solver, with a self-motivated attitude that drives him to excel in his work. Prior to joining Chubb, Kapil worked as a Software Engineer at Pitney Bowes and as a Machine Learning Engineer at Artivatic. At Artivatic, he collected data from the National Family Health Index Survey and performed exploratory data analytics to calculate the impact of poor sanitation, latrine facilities, and water sources on infant and maternal mortality rates in India. He also implemented machine learning algorithms to assess the risk of sanitation for each PIN code in a particular state and calculated the impact of air quality on public health. Kapil holds a Master of Computer Applications degree from the National Institute of Technology Raipur and a Bachelor of Computer Applications degree from the University of Rajasthan. He has a strong tech stack that includes ML, Data Scientist, Research Scientist, SQL, Python, Software Engineer, and C. Overall, Kapil Ahuja is a highly skilled and motivated Data Scientist and MLOPS Engineer with a proven track record of delivering high-quality solutions to complex business problems.