Machine Learning Engineer - North American Integrated Analytics Team

Munich Re CanadaToronto, ON16 days ago

In keeping with our global position as in industry leader and innovator, Munich Re is driving transformative change in the life insurance industry through data science. The North American Integrated Analytics Team is looking for a Machine Learning Engineer for their Toronto or New York office.



Toronto, Canada Or New York City, US


As a Machine Learning Engineer, you will apply statistical techniques and machine learning to build solutions to core challenges in the life insurance industry. You will be immersed in real-time business problems while engaged in a collaborative approach to delivering world-class, innovative solutions for our North American operations and clients. We see the use of data as instrumental in making it easier for people to buy life insurance and to expand the number of people insured.

Your job

  • Design, develop, and deploy consumer-facing machine learning products
  • Apply advanced statistical and machine learning techniques to build models for underwriting, pricing, and claims management
  • Help us to drive innovation, enabling new underwriting paradigms, distribution models, and data management
  • Proactively research new ways of modeling data to unlock actionable insights or improve processes.
  • Collaborate across Munich Re functions to create machine learning services
  • Work with existing data science groups at Munich Re and collaborate with internal partners to leverage technological and machine learning capabilities

Your profile

The successful candidate will demonstrate a natural desire to provide exceptional client service through his/her energy, enthusiasm, and initiative.

In addition, we are looking for the following qualifications:

  • Undergraduate Degree in Computer Science, Engineering, Statistics, or Applied Mathematics, plus 3 years' experience OR Graduate Degree in Computer Science, Engineering, Statistics, or Applied Mathematics, plus 1 years' experience
  • Expertise in advanced predictive analytics techniques
  • Ability to write robust code for deployable services in Python; working knowledge of SQL (familiarity with multiple languages considered an asset)
  • Experience working with analytics through the modeling lifecycle including gathering data, design, recommendations, testing, implementation, communication, monitoring, and retraining.
  • Experience with cloud computing platforms (e.g., Microsoft Azure, AWS, GCP)
  • Experience with software engineering best practices including Git, Docker, CI/CD, test driven development, and code review
  • Familiarity with big data technologies (e.g., Apache Spark, Airflow, etc.), natural language processing and deep learning frameworks (e.g., TensorFlow, PyTorch) is an asset but not required.
  • Strong communication skills
  • Agility to work across multiple internal teams.
  • The ability to learn quickly
  • A drive to make a difference
  • Thrive in a dynamic environment and successfully deliver on multiple assignments under deadlines

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