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Open nowFirst seen 46 hours ago

Data Scientist, Analytics & Modeling

ABACUS digital24 open roles

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Your applicationOpen nowData Scientist, Analytics & ModelingABACUS digital

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  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

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The clock on this job

Early applications get read.

11.8% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.8%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: first seen 46 hours ago

The posting

About this Role

At ABACUS digital, we are working hard to provide better access to credit for everyone, aiming to solve one of the fundamental problems in Thailand – financial inclusion. Our flagship product is the digital lending application, MoneyThunder, that is already used by more than one million people in Thailand. We are at the stage of scaling the impact beyond the first million.

One of the core technologies that power MoneyThunder is AI/ML and we strive to use machine learning to improve every aspect of our product, ranging from credit risks and collection strategy to user experience and user acquisition. As we scale, we are planning to build a next-generation machine learning platform with even higher scalability and velocity to support more use cases of AI/ML in our business. And we are looking for talents like you to bring passion in software engineering and AI/ML and join our mission to build innovative technology for a good social cause.

What will you do

  • Build end-to-end machine learning or statistical models to use in our digital products from problem formulation, data collection, model development, and implementation.
  • Conduct research and analysis on various data sources to find predictive signals to help improve model performance.
  • Collaborate with other business units to help formulate business problems into data analytic, experimentation, or modeling problems.

Who we are looking for

  • Strong background in probability, statistics, machine learning, or other quantitative areas of study.
  • Good understanding of end-to-end model development process from problem formulation to implementation.
  • Ability to communicate effectively with business units to help formulate problems into data analytics, experiments, or modeling problems.
  • Background in finance is optional, but one should have a strong interest in our business and fintech industry.
  • Programming skills in Python and SQL
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