Data Scientist

Big data, artificial intelligence 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 centres 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, non-life and health. An exciting opportunity exists for a data scientist with advanced analytics skills to join Munich Re's regional analytics centre (RAC) of competence located in Singapore. The RAC supports Munich Re's Asia-Pacific (including China and Australia), Middle East and Africa business life and health business region. 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.

Using advanced analytics methods to derive actionable insights from existing and new sources of data, the role will contribute towards new services and business models. Predictive analytics applications will span the entire insurance value chain from transforming the customer experience during underwriting, cross-selling, pricing and experience analysis, lapse prevention through to claims management decisions. In this position you will cooperate closely with our clients, actuaries, underwriters, client managers, the IT department, other analytics teams worldwide including at our head office in Munich.

You will apply Machine Learning (ML) and Deep Learning (DL) methods to interpret all types of data (structured, unstructured, images, etc.) and build solutions to and solve real problems our clients are facing today.

You will play a leading role in the execution of the full modeling cycle, including the integration of data, selection and application of predictive modeling techniques, model validation and deployment, and engagement with clients on results. As we continue to innovate and advance our capabilities, this role will also leverage Generative AI (Gen AI) technologies to further enhance our predictive analytics and machine learning initiatives. This will involve exploring the application of Gen AI in areas such underwriting and claims. By combining traditional analytics with the latest advancements in Gen AI, we aim to unlock new levels of business value, elevate customer experience, create efficiency gains for domain experts and stay at the forefront of the rapidly evolving analytics landscape.

Your Role

• The opportunity to be a data scientist in a vibrant, leading global reinsurance company with diverse data to enable innovative data analytics
• Develop insurance business solutions based upon insight discovered from data
• Active participation and management of projects in the fields of statistics, ML and DL
• Development and implementation of solutions that enable operational units to increase quantity and quality of new business
• Supporting and advising the business units in applying the latest research methods and providing a central source for specialized know-how, tools and techniques for data analytics
• Presentation of statistical, ML and DL solutions to internal and external stakeholders
• Networking with already existing data-intensive units in the area of analysis and reporting, as well as with IT to form an analytics community.
• Collaborate with internal partners in Life and Health and the data analytics centre in Munich to leverage capabilities in big data technology
• Opportunities to lead and deploy GenAI projects across insurance value chain

Your Profile

• Preference for Master's or Ph.D. in data science / advanced data analytics but other fields will be considered including statistics, applied mathematics, information technology, engineering, computer science, or a comparable discipline.

Experience:

• Proven experience managing analytics projects end to end
• Very good theoretical knowledge of AI, ML and DL methods
• Hands-on coding in R, Python, SQL (e.g. ETL), etc.
• Experienced in carrying out exploratory data analysis, model development and visualization in Jupyter Notebooks (Python and R) & Databricks
• MUST have demonstrable experience in coding and applying traditional regressions (e.g. GLMs), ML (decision trees, random forest, boosted trees, etc.), natural language processing, DL
• Experience in Gen AI uses cases around information retrieval , summarisation & inference
• and in understanding of LLMs and its applications will be an added advantage
• Hands on experience coding front end, back end, API integrations. Full stack developer experience is an advantage
• Visualization in Power BI, D3.js, Dash, JavaScript, etc. is an advantage
• Working on data science virtual machines on the cloud (Azure, AWS, etc.)
• Understanding of RESTful APIs and microservices is an advantage
• Demonstrable Kaggle / Git / analytics blogs and repos are an advantage
• Experience in insurance/reinsurance industry would be an advantage and specifically on the topics of underwriting and claims automation and fraud detection
• Ability to deliver under short but reasonable timelines
• Cappacity for innovation, entrepreneurial mindset, forward-looking, enjoy working in a team

Stakeholder management:

• Working with multiple stakeholders across the analytics lifecycle

. Strong communication in:

• Documenting analytics results (e.g. MSWord, PowerPoint, Notebooks, etc.)
• Verbally explaining analytics concepts and results to non-technical audiences and domain experts and translating analytics results into business solutions

Our Benefits

• Flexible and hybrid working arrangement
• Generous annual leave allowance
• Comprehensive dental, life and health insurance coverage

At Munich Re, we embrace, and value, the interaction of diverse backgrounds, experiences, perspectives and thought. This interaction is our foundation. Of our open culture and spirit of partnership. Of how our teams are built and cultivated. Of how we are supported and developed. And at the center of this interaction is each of us