Participate in and conduct research on decision-quality analysis and continuous improvement of the project
Develop and research statistical algorithms and machine learning models; use SQL and Python to validate and build production applications of large language models (LLMs)
Extract and analyze data to validate hypotheses and deliver quantifiable, actionable conclusions with clear implementation directions
Assist in producing analytical reports and technical documentation; collaborate with the team to drive project progress

Master's degree or above in a STEM field (CS, Statistics, Data Science, Applied Mathematics, EE, or related)
Python proficiency: able to independently write data processing and analysis scripts (pandas, numpy, etc.)
At least one end-to-end project where you drove the work from start to finish with a tangible deliverable
Statistics / ML fundamentals: solid understanding of statistical models, machine learning model training and classification evaluation metrics (precision, recall, confusion matrix, FP/FN, and their business implications)
English reading and writing fluency (all project documentation and code are in English)
Strong teamwork mindset and a sense of ownership/responsibility for the project
Experience using AI coding assistants (Copilot / Cursor / Claude / ChatGPT) on real projects with a verification mindset (not blindly trusting AI output)
LLM / Prompt Engineering / Agent project experience
SQL data extraction experience
Background in financial risk, KYC, compliance, or anti-fraud

Competitive salary and company benefits
Work-from-home arrangement (the arrangement may vary depending on the work nature of the business team)

Data Scientist, AI Agent Quality

Key skills