(Senior) Data Scientist

Reporting to the Senior Data Scientist & Analytics Manager, 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, you will also leverage Generative AI (Gen AI) technologies to enhance our predictive analytics and machine learning initiatives. This will involve exploring the application of Gen AI in areas such as 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

• Develop insurance business solutions based upon insights discovered from data.
• Active participation and management of projects in the fields of statistics, ML, and DL.
• Develop and implement solutions that enable operational units to increase the quantity and quality of new business.
• Support and advise the business units in applying the latest research methods and providing a central source for specialized know-how, tools, and techniques for data analytics.
• Present statistical, ML, and DL solutions to internal and external stakeholders.
• Network with 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 the insurance value chain.

Your Profile

• Master’s or Ph.D. in data science / advanced data analytics or fields such as statistics, applied mathematics, information technology, engineering, or computer science.
• More than 5 years of industry data science / AI / ML experience.
• Proven experience managing analytics projects end to end.
• Very good theoretical knowledge of AI, ML, and DL methods.
• At least 7 years of hands-on coding in R, Python, SQL (e.g. ETL), etc.
• Proven experience overseeing less experienced data scientists.
• Experienced in carrying out exploratory data analysis, model development, and visualization in Jupyter Notebooks (Python and R) & Databricks.
• 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 use cases around information retrieval, summarization & inference, and understanding of LLMs and their applications will be an added 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 the insurance/reinsurance industry would be an advantage, specifically on the topics of underwriting and claims automation and fraud detection.
• Working with multiple stakeholders across the analytics lifecycle.
• Strong communication skills in documenting analytics results and verbally explaining analytics concepts and results to non-technical audiences and domain experts, translating analytics results into business solutions.
• Ability to deliver under short but reasonable timelines.
• Capacity for innovation, entrepreneurial mindset, forward-looking, and enjoy working in a team.
• Willingness to travel within Asia for short periods.

Data Science at Munich Re

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 state-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, and 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 solve real problems our clients are facing today.

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, how our teams are built and cultivated, how we are supported and developed. And at the centre of this interaction is each of us.