Role Overview:
You will be responsible for identifying opportunities for business growth, supporting the business in meeting budgets through analytical insights, and communicating results and ideas to key decision makers. You will conduct regular portfolio health check-ups through business insights, identify areas of growth and sluggishness within the portfolio, drive insight-led actionables to achieve portfolio targets, and support stakeholders in business reviews. Additionally, you will support key business initiatives for data-driven decision-making.

Key Responsibilities:
- Structure, define, and execute data analysis to uncover insights and inform decision-making for the digital bank
- Engage with business and product teams on problem formulation and create solution frameworks
- Collaborate with regional and local counterparts to define and align performance metrics
- Support ad-hoc data requests for management meetings
- Formulate requirements and work with data engineering and technology teams to develop and validate automated data pipelines for business performance dashboards
- Design A/B test experiments to test model effectiveness and analyze to identify target segments
- Drive the testing and deployment of machine learning products into production
- Understand the product journeys and help the business improve customer experience

Qualifications Required:
- 3 years of experience in Data Science/Analytics (Consumer Banking, Ecommerce, Retail, Telecoms) with a demonstrated track record of generating value through data-driven solutions
- B.Sc./ M.Sc. or equivalent degree in Statistics, Analytics, Applied Mathematics, Operation Research, or equivalent quantitative fields preferred
- Prior working experience in analytics is a must
- Full understanding of applications of data science/machine learning/artificial intelligence solutions to various business problems
- Proficiency in using databases like Teradata, NoSQL, and Hadoop using SQL, Hive, PySpark, etc.
- Programming experience in Python, R, PySpark, TensorFlow, or other machine learning-oriented programming languages/platforms
- Good understanding of technology tools especially those related to analytics, data & modeling
- Ability to communicate complex analysis/models across a diverse team
- Good written and oral communication skills
- Full understanding of at least one banking product
- Strong academic background
- Self-motivated, adaptable, focused, and well-organized
- Possess a creative bent of mind and be a strategic thinker Role Overview:
You will be responsible for identifying opportunities for business growth, supporting the business in meeting budgets through analytical insights, and communicating results and ideas to key decision makers. You will conduct regular portfolio health check-ups through business insights, identify areas of growth and sluggishness within the portfolio, drive insight-led actionables to achieve portfolio targets, and support stakeholders in business reviews. Additionally, you will support key business initiatives for data-driven decision-making.

Key Responsibilities:
- Structure, define, and execute data analysis to uncover insights and inform decision-making for the digital bank
- Engage with business and product teams on problem formulation and create solution frameworks
- Collaborate with regional and local counterparts to define and align performance metrics
- Support ad-hoc data requests for management meetings
- Formulate requirements and work with data engineering and technology teams to develop and validate automated data pipelines for business performance dashboards
- Design A/B test experiments to test model effectiveness and analyze to identify target segments
- Drive the testing and deployment of machine learning products into production
- Understand the product journeys and help the business improve customer experience

Qualifications Required:
- 3 years of experience in Data Science/Analytics (Consumer Banking, Ecommerce, Retail, Telecoms) with a demonstrated track record of generating value through data-driven solutions
- B.Sc./ M.Sc. or equivalent degree in Statistics, Analytics, Applied Mathematics, Operation Research, or equivalent quantitative fields preferred
- Prior working experience in analytics is a must
- Full understanding of applications of data science/machine learning/artificial intelligence solutions to various business problems
- Proficiency in using databases like Teradata, NoSQL, and Hadoop using SQL, Hive, PySpark, etc.
- Programming experience in Python, R, PySpark, TensorFlow, or other machine learning-oriented programming languages/platforms
- Good understanding of technology tools especially those related to analytics, data & modeling
- Ability to communicate complex analysis/models across a diverse team
- Good written and oral communication skills
- Full understanding of at least one banking product
- Strong academic background
- Self-motivated, adaptable, focused, and well