Data Science Analyst

Description : Assist in developing and maintaining advanced analytics tools by utilizing machine learning and predictive analytics techniques. It results in pricing enhancement, early fraud detection, loss control efficiency, customer experience improvement, better broker selection, and better claims reserving. Develop, implement, and maintain predictive and machine learning models. Utilize predictive analytic and machine learning techniques on risk selection, pricing refinement, claims insights, and business decisions. Provide visualization solutions for monitoring model results and managing portfolio performance. Participate in special projects and perform additional duties as required. Requirements : Bachelor's degree and with data science, computer science, math, engineering or related degree required. Master's degree in data science preferred. 2-3 years of data science experience specialized in data mining and machine learning required Experience with insurance background preferred. Good understanding of predictive modeling algorithms and machine learning techniques including classification, clustering, regression, decision tree, random forest, and deep learning etc. Proficiency in manipulating big data (including structured and unstructured data) from various sources. Proficiency in R, Python, SQL, VBA, Tableau, and Power BI. Good verbal and written communication skills.