Data Scientist - TrueMoney Wallet

About Us

Our Ascend vision is to create life opportunities with innovative digital services. Operating in Southeast Asia, we are able to help one of the world’s largest populations of underbanked, the people from some of the poorest provinces who are disregarded by traditional banks. So many lives are waiting for our help.

In 2018, we served over 30 million customers in 6 countries (Thailand, Cambodia, Myanmar, Vietnam, Indonesia, Philippines), and processed over 4.5 billion USD. This makes us by far the largest fintech company in SE Asia and growing quickly.

As a member of our talented Data Analytics & AI team, you will play a crucial role in bringing this vision to life by harnessing advanced data-driven technologies and AI solutions. At Ascend, you will join a team directly responsible for improving the lives of millions through innovation and insights.

Responsibilities:

● Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.

● Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business

strategies.

● Assess the effectiveness and accuracy of new data sources and data gathering techniques.

● Develop custom data models and algorithms to apply to data sets.

● Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting, and other business outcomes.

● Develop company A/B testing framework and test model quality.

● Coordinate with different functional teams to implement models and monitor outcomes.

● Develop processes and tools to monitor and analyze model performance and data accuracy.

Qualification:

● We’re looking for someone with 5-7 years of experience manipulating data sets and building statistical models.

● Has a Master’s degree or PHD in Statistics, Mathematics, Computer Science or another quantitative field, and is familiar with the following software/tools:

● Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.

● Experience querying databases and using statistical computer languages: R, Python, SQL, etc.

● Experience using web services: Redshift, S3, Spark, DigitalOcean, etc.