Senior Data Scientist
2 months ago
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.
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
- 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. Candidates with actuarial training and subsequent proficiency in data science / advanced analytics will also be considered:
- Experience:
- More than 5 years of industry data science / AI / machine learning (ML) experience
- At least 7 years of hands-on coding in R, Python, SQL (e.g. ETL), etc.
- Very good theoretical knowledge of AI / ML / deep learning (DL)
- 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 managing complex analytics projects end to end and professionally handling stakeholder management
- Prior experience overseeing junior data scientists
- Experience in carrying out exploratory data analysis, model development and visualization in Jupyter Notebooks (Python and R)
- Demonstrated experience in understanding of LLMs and its applications will be an added advantage
- Visualization in Power BI, Dash, 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
- Stakeholder management:
- Working with multiple business stakeholders across the analytics lifecycle in delivering the project
- Strong communication in:
- Verbally explaining analytics concepts and results to non-technical audiences and domain experts and translating analytics results into business solutions
- Documenting analytics results (e.g. MSWord, PowerPoint, Notebooks, etc.)
- Expected to take ownership (self-starter) to lead AI initiatives and support wider project teams to successful outcomes
- Ability to deliver under short but reasonable timelines
- Willingness to travel within Asia for short periods
- Flexible and hybrid working arrangements
- Generous annual leave allowance
- Competitive dental, life and health insurance coverage
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