GenAI Data Scientist - 12-Month Contract

Münchener Rückversicherungs-Gesellschaft; Singapore; On-site; SGD 70,000 - 90,000; Full time

Job summary

A leading global reinsurance company in Singapore is seeking a data scientist to join their analytics center. This role involves developing business solutions using data insights, participating in ML projects, and leveraging GenAI technologies to enhance predictive analytics. Ideal candidates will have 2+ years in data science, experience in Python, and a strong grasp of machine learning concepts. Join a vibrant team at the forefront of analytics innovation within the insurance industry.

Qualifications

• 2+ years of industry experience in data science/AI/ML.
• Hands-on experience in Python and full stack development.
• Strong understanding of GenAI, ML, and deep learning.

Responsibilities

• Develop insurance business solutions based on data insights.
• Participate in and manage projects in statistics, ML, and DL.
• Collaborate with internal partners to leverage big data capabilities.

Skills

Python

Machine Learning

Deep Learning

GenAI

Stakeholder management

Education

Bachelor's or Master's or Ph.D. in data science/AI

Tools

RESTful APIs

JavaScript

Job description

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 vital 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 manage and deploy GenAI projects across insurance value chain

Your Profile

• Bachelor’s or Master’s or Ph.D. in data science / AI, but other fields will be considered including statistics, applied mathematics, information technology, engineering, computer science, or a comparable discipline.

Experience:

• Ideally more than 2 years of industry experience in data science / AI / ML experience
• Hands on experience in Python coding front end, back end, API integrations. Full stack developer experience is an advantage. Visualization in JavaScript, etc. is an advantage
• Very good theoretical knowledge of GenAI, ML and deep learning
• Understanding of RESTful APIs and microservices is an advantage
• Experience in Gen AI use cases and agentic workflows involving information retrieval , summarisation, inference and in understanding LLMs and their applications will be an added 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 claims automation

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

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