Credit & Data Science

Data Scientist

Bangkok, or Jakarta
Work Type: Full Time

We’re a financial services company leveraging cutting-edge technology to bring payment solutions to the underserved Southeast Asia market. The team is a diverse and carefully selected group of world-class finance and tech professionals. Our blossoming tech team, led by top-tier international talent based in Bangkok, are grinding away, preparing to launch our first product. The environment is fast-paced and quality oriented, driven by our passionate team. We’re learning, breaking, fixing, growing, and loving it.

Job Description:

  • Research and develop algorithms to solve complex business problems
  • Build machine learning pipelines to process data, train models, compare experiments, and serve models
  • Implement A/B tests of deployed models
  • Build pipelines for automated data collection
  • Work with stakeholders to understand the problems and come up with plans to solve them with data
  • Create reports/dashboards to present valuable insights to stakeholders


  • Bachelor’s, Master’s, or PhD in Statistics, Applied Mathematics, Financial Engineering, Computer Science, Electrical Engineering, or related fields
  • At least 4 years of experience working in Data Science
  • Knowledge and experience in training and applying Machine & Deep Learning algorithms (e.g. Logistic Regressions, Decision Trees, Bagging, SVMs, PCA, CNNs, RNNs, and Transformers) to solve complex problems
  • Knowledge of statistical techniques and concepts such as regression, time series analysis, statistical distributions, statistical tests
  • Experience using R, Python, or SQL to process data to draw insights from large datasets
  • Expertise in one of the Deep Learning languages: Tensorflow, Pytorch, Mxnet
  • Experience building data pipelines on AWS, GCP, or Azure
  • Experience working with a Distributed Computing tool such as Hadoop, MapReduce, and Spark
  • Experience with Deep Reinforcement Learning or Graph Neural Networks is a big plus
  • Experience using MLOps tools such as Kubeflow, MLFlow, or Sagemaker is a big plus
  • Knowledge of Credit Risk Modeling is a big plus

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