(Senior) Data Scientist

2 weeks ago


Singapore Munich Re Full time

(Senior) Data Scientist

**Company**
Munich Re
**Location**
Singapore, Singapore

**Your Role**
- Develop insurance business solutions based upon insight 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 quantity and quality of new business
- Present statistical, ML and DL solutions to internal and external stakeholders
- Network 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**
- 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 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
- Experience in Gen AI uses cases around information retrieval, summarisation & inference
- 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
- Stakeholder management:

- Working with multiple stakeholders across the analytics lifecycle
- Strong communication in:

- Documenting analytics results
- Verbally explaining analytics concepts and results to non-technical audiences and domain experts and translating analytics results into business solutions
- Ability to deliver under short but reasonable timelines
- Capacity for innovation, entrepreneurial mindset, forward-looking, enjoy working in a team
- Willingness to travel within Asia for short periods

**Our Benefits**
- Flexible and hybrid working arrangements
- Generous annual leave allowance
- Comprehensive dental, life and health insurance coverage

**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 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.
- 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 centre of this interaction is each of us._



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