Lead Machine Learning Engineer, Life and Health

**Lead Machine Learning Engineer, Life and Health Regional AI/Analytics Centre**:Career Level 3

**Location**Singapore, Singapore

Artificial intelligence (AI) and advanced analytics are transforming the insurance industry across the value chain. Munich Re is at the forefront of this trend, having made a significant investment in start-of-the-art analytics infrastructure and software, central and regional analytics centers of competence and several successful analytics initiatives with its clients worldwide.

Munich Re has experienced exponential growth in demand for analytics pilots from its clients in life and health. An exciting opportunity exists for a data scientist and engineers with advanced analytics skills to join Munich Re’s regional Life and Health analytics center (RAC) of competence located in Singapore. The RAC supports Munich Re’s Life and Health clients in Asia-Pacific, Middle East and Africa business. As such you will work in an agile and innovative area, gaining exposure to a wide variety of business problems, other teams of Munich Re, clients and geographies.

Your job
- Regional Lead ML engineer in a vibrant, leading global reinsurance company with diverse data to enable innovative AI and digital solutions.
- Oversee the AI technology roadmap for the region, ensuring synergies between existing technologies are maximized and a coherent, cost-effective technology roadmap
- Play a lead role in the development of a modern AI platform for operationalizing Munich Re AI solutions in client environments
- Hand-on data engineering and MLOps support to the data scientists to ensure successful deployment of AI solutions
- Collaborate with internal technology partners and the data analytics center in Munich to leverage capabilities in analytics technology and as the team expands, potentially to manage/lead team of junior ML engineers. You will have the opportunity to work with Munich Re’s leading team in underwriting technology
- Design, develop, and deploy consumer-facing machine learning products
- Proactively research MLOps best practices and related technical architecture designs
- Collaborate across Munich Re functions to create machine learning services
- Presentation of deployment solutions to internal and external stakeholders
- Networking with already existing data engineering units across the globe

**Profile**:

- Postgraduate (preferably Masters or PhD) degree in computer science, computer engineering, information systems, information technology, equivalent field or substantial coursework in relevant disciplines. Should have basic theoretical knowledge / familiarity with AI, ML and DL methods
- Experience:

- 3-5 years of hands-on experience as a Data Engineer, DevOps engineer with a focus in deploying AI/ML solutions to production in a DevOps environment with knowledge of CI/CD pipelines.
- Experience in designing machine learning platforms and data pipelines at scale
- Expertise with Kubernetes (including network security policies, certificate management, RBAC, Helm), CI/CD automation, Docker, and microservice architecture.
- Hands-on experience in implementing CI/CD pipelines using Azure DevOps with a focus on testing, code quality, and security
- Ability to write robust code for deployable services in Python. C++ and Java would be an advantage
- Advanced skills in working with relational SQL data stores (Microsoft SQL, MySQL or similar) & NoSQL databases such as Cosmos DB
- Experience deploying cloud infrastructure, preferably using Azure.
- Experience in conducting UAT and knowledge of testing methodologies
- Knowledge in building frontend web apps using react.JS, D3.js, Dash, JavaScript, etc. is an advantage
- Leadership experience overseeing junior engineers is an advantage
- Familiarity with big data technologies (ex. Apache Spark, Airflow, etc), natural language processing and deep learning frameworks (ex. Tensorflow, Pytorch) is an advantage
- Experience in the insurance/reinsurance industry, specifically on the topics of underwriting, claims automation and fraud detection would be an advantage
- Strong communication:

- Documenting analytics deployment solution (e.g. MSWord, PowerPoint, etc.)
- Verbally explaining solution architectures & concepts to non-technical audiences and domain experts
- Good command of English essential
- Willingness to travel within Asia for short periods
- The ability to learn quickly, drive to make a difference and successfully deliver on multiple assignments under deadlines
- Capacity for innovation, entrepreneurial mindset, forward-looking, enjoy working in a team

About us

Find out **Who we are, What we do, Our Strategy and How we can Support & Reward** you.

Our business model is based on the combination of primary insurance and reinsurance under one roof. We take on risks worldwide of every type and complexity, and our experience, financial strength, efficiency and first-class service make us the first choice for all matters relating to