1. Participate in the development of machine learning model and applied it in predicting and preventing fraud
2. Develop key metrics to track the performance of fraud and collaborate with engineering team, business team to meet the set goals.
3. Participate in the full development cycle: design, develop, deploy, experiment and analyze.
1. Master’s degree (or PhD) in Statistics, Mathematics, Operations Research, Computer Science, Economics or other quantitative discipline. Bachelor’s degree with significant relevant experience will be considered.
2. Proficient in at least one or more of the programming languages, such as C++, Python. Familiar with Hive, Spark, Tensorflow, etc
3. Familiar with one or more of the following technologies - machine learning, NLP, data mining, search, recommendation, anti-fraud, etc.
4. Possess strong analytical and problem-solving capabilities and keen to solve challenging problems
5. 3+ years of experience in developing machine learning based solutions for fraud detection.