Data Scientist - Consumer Analytics

Bangkok Bank (Bangkok City, Thailand)

Bangkok, Thailand

Discover Bangkok Bank – Thailand’s largest commercial bank and one of the leading commercial banks in Southeast Asia. A pioneer bank with long progress of the country. Bangkok Bank has grown and matured with Thai people and their business interests and today is renowned for its size, stability and partnership approach. The bank is driving innovation in new products and services and building on its inherent scale advantages to meet the challenges of a changing financial landscape and consolidate its leadership position for the future.

Detail posisi

Technology is changing every day and Bangkok Bank is determined to be at the forefront of these changes. Millions of customers use our multi award willing Banking product on a daily basis. This is just the start - we are aggressively using technology to delight our customers in all segments.

Kewajiban

• Analyze customer-level data with AI / ML / Data-mining techniques to understand customer insights, extract customer’ needs and pains.
• Apply descriptive and predictive modeling techniques to extend the right offer for targeted campaign to enhance customer experience.
• Perform data analytics to support product marketing, campaign management, digital marketing, and related departments to help generate revenue.
• Develop A/B testing framework and evaluate models.
• Present key findings and recommendations to business parties and management on customer relationship management approach and strategic planning.
• Develops and deploy E2E data science / E2E advanced analytic model
• Develop the tools to monitor and analyze model performance and data quality.

Kualifikasi

• Bachelor’s Degree or higher in Data Mining, Statistics, Engineering, Economics, IT or any related field
• Experience in Data Analytics, Data Mining, Data Science will be an advantage
• Good analytical skills with business interest and mindset
• Good communication skills including ability to provide clear, and business-friendly explanation of complex analysis