Data Scientist is responsible for driving new and innovative approaches to how understand, interact and service its customers. In addition, to distribute through the optimization of analytics to drive business insights.
The Data Scientist is expected to provide enterprise-level consulting to MetLife business executives on the design, development and implementation. Analyzing models and insights, and simplifying for business implementation/integration.
- Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
- Identify, hypothesize, and implement the analytics business problems, secure proof of concepts and project delivery
- Deliver analytical solutions for the business, creating compelling explanations and plans to drive adoption in the business
- Understand and leverage MetLife data environment
- Selecting features, building and optimizing classifiers using machine learning techniques
- Use statistical methods to conduct descriptive, predictive and prescriptive model building, and summarize/present findings in an impactful manner.
- Machine learning using state-of-the-art methods
- Coordinate with different functional teams to build models and monitor outcomes.
- Extract data from multiple systems for MetLife organizational activities
- Support business leader’s benefits realization of improved sales (new business ANP), value of new business (VNB), operational efficiency, Net promoter Score (NPS), Customer Centricity and other agreed measures within the Data Analytics program
- Team player, able to support wider needs in visualization, data management and BI as the need arises
- Be part of the global analytics community, presenting and sharing best practices to improve global and local capability
- 3-5 years of experience in the field of advanced quantitative techniques. It’s a plus if you have worked for leading global academic institutes, corporate innovation research labs, analytics organizations of large corporate or in consulting companies in analytics roles
Business Knowledge/Technical Skills:
- Deep technical competency in quantitative methods and/or business analytics and problem-solving skills in industrial settings
- Proven ability in model building and application experience in data mining techniques and tools (e.g., SQL, R, Python)
- Competent programming aptitude with excellent computation and data mining skills
- Strong analytical, problem-solving and organizational skills, understands what it takes to deliver software with exposure to large-scale systems
- Very good communicator in Business Japanese
- Self-motivated to continuously upgrade one’s domain knowledge, keep abreast of latest developments in the field and evaluate its application in the business area on a consistent basis
- Demonstrated ability to establish relationships and build rapport in order to influence colleagues at all levels, uncover business issues and identify needs
- Demonstrated ability to present and communicate concisely and clearly with all levels of financial, non-financial, technical and executive audiences
- Bachelor’s degree in any advanced quantitative modeling-oriented discipline such as Statistics, Marketing Science, Operation Research, Econometrics, Stochastic Finance, Machine learning, Computer science, Digital media analytics
- Statistical package software (e.g., SAS)
- Business-level English is a plus
- Insurance industry domain knowledge
- Visualization tools (QlikView, Qlik Sense, Power BI) advantageous
- Hands-on experience with Spark, or the Hadoop ecosystem advantageous
- Graduate degree in any advanced quantitative modeling-oriented discipline such as above