This program is for college graduates from December 2016 or May 2017. For internal purposes this posting should be used to refer external candidates only. As one of the world's leading reinsurance companies, Munich Re is dedicated to training all employees to reach the highest levels of insurance and reinsurance knowledge and to bringing that knowledge and expertise to our clients. The International Graduate Trainee Programme is one way of accomplishing this critical goal. The program offers a comprehensive training program for college graduates. Successful Predictive Analytics track candidates will complete a two year program which includes classroom (20%) and hands-on (80%) training leading to careers in Predictive Analytics. This is a leadership development program providing participants technical training, business skills training and experiential training in a broad range of departments throughout the Company.
Attend scheduled classroom training.
• Participates actively in the presentation/discussion. • Demonstrates that (s)he has read the pre-reading material, if applicable. • Asks questions which demonstrate interest in developing a full understanding of the material.
Actively participate in various scheduled rotational assignments.
• Reviews rotation guide with rotation manager/specialist to assure that expectations are consistent. • Asks questions which demonstrate interest in developing a full understanding of the subject matter/techniques. • Completes assigned work/tasks in a correct, timely and thorough fashion.
Passes selected industry exams.
• Those pursuing the Predictive Analytics Track will have the option of completing: ·Two actuarial exams during the two-year program or ·Completing 12 credit hours per semester of graduate level classes on topics approved by manager (with paid study time allowed) or 6 credit hours per semester (without paid study time) ·Earning the online designation through coursera.org “Machine Learning” offered by U. of Washington
Applicants should be graduating December 2016 or May 2017.
Your submission must be received by October 15, 2016 to be considered.