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VP/AVP, Data Scientist, Human Decision Science, Group Human Resources
VP/AVP, Data Scientist, Human Decision Science, Group Human Resources
The VP/AVP, Data Scientist will be responsible for partnering with HR business partners to assess human capital needs and apply data analytics. This role involves defining analytical strategies, developing statistical models to identify risks, and presenting actionable recommendations to senior management. The ideal candidate will have at least 5 years of experience in statistical modeling and be proficient in Python, Spark, R, and SQL.
About the role
Business Function
Group Human Resources has the important role of attracting, retaining, and nurturing talent to ensure that DBS continues to be a competitive employer in Asia. With a well-established team of HR partners, we support and deliver effective people-based solutions and services across businesses. Our goal is to build a high-performance organisation by empowering and engaging our employees. Because we believe that banking is about people.
Responsibilities
- Partner with HR business partners and specialists to assess human capital needs and identify opportunities to apply data analytics
- Define analytical strategy, problem statements and hypotheses to address identified opportunities, including analytical approaches, data and technology requirements
- Develop models and perform statistical analysis to identify key areas of risk and predict risk events, across a range of banking functions
- Design and put in place tracking and feedback mechanisms to allow for capturing of actions and impact on business outcomes due to the implementation of analytics solutions
- Present key findings to senior management and/or other stakeholders with actionable recommendations
- Work with other data scientists and data translators to drive and operationalize analytical outputs
Requirements
- At least 5 years of working experience in building and implementing various statistical models, and working with large amounts of data
- Mathematical problem formulation skills
- Deep understanding of mathematical and modelling techniques. An ability to translate business problems into mathematical formulations. Familiar with data manipulation and analysis. Ability to approach data in creative ways and from different angles for use in predictive and prescriptive modelling
- Experience in building and operationalizing the analytical capability
- Programming experience in Python, Spark, R or other statistical software. Proficient in SQL
- Experience working with unstructured datasets with knowledge in text mining and text analysis is preferred
- Familiar with Hadoop, Java, Python, SQL, Hive, and MariaDB. Understanding of ETL (extract, transformation, loading) of data including tools
- Able to present analysis in a manner accessible by non-statisticians through data visualization techniques. Excellent verbal and written communication skills
- Independent self-starter with ability to multi-task and has a ‘can-do’ attitude