1. Formulate classic statistical methods & apply mathematical/optimization modeling to policy decision making/other functions of business operation solutions;
2. Collect/analyze data from operation systems to develop support tools using statistical analysis/simulation methods/outcome visualization on historical datasets;
3. Define data requirements/operational problems, validate information, implement judgment/statistical tests to solve business problems & optimize allocation of resources;
4. Develop fraud detection models using machine learning algorithms, identify potential/existing operational problems to improve/reformulate mathematical models;
5. Design procedures & define quantitative metrics to control fraud/compliance risk levels;
6. Analyze business pinpoints, provide data analysis reports/recommendations to management & other departments.

Required: MS in Operations Research/Applied Mathematics/Statistics or a related field. In-depth knowledge of probability & statistics/machine learning; Strong ability to collect/interpret large/complex datasets & perform business analysis; Excellent skills in data quality/quantitative risk management & feature engineering for fraud mitigation/identification; Expertise in analytical methodologies (i.e., statistics/data modeling/forecasting/optimization); Proficient in Python/SQL/R/NumPy/Pandas/Scikit-learn/Keras/PyTorch/Tensorflow.

Apply: family@fluz.app