Anti-fraud Data Scientist

2 weeks ago

Singapore Shopee Full time

Department Engineering and Technology- LevelExperienced (Individual Contributor)- LocationSingaporeThe Engineering and Technology team is at the core of the Shopee platform development. The team is made up of a group of passionate engineers from all over the world, striving to build the best systems with the most suitable technologies. Our engineers do not merely solve problems at hand; We build foundations for a long-lasting future. We don't limit ourselves on what we can or can't do; we take matters into our own hands even if it means drilling down to the bottom layer of the computing platform. Shopee's hyper-growing business scale has transformed most "innocent" problems into huge technical challenges, and there is no better place to experience it first-hand if you love technologies as much as we do.
- Responsible for implementing solutions to detect various fraudulent/risky behaviors on Shopee, including promotion fraud, logistics fraud, payment fraud, and account fraud.
- Conduct data mining and extract meaningful features from big data.
- Build and design machine learning, deep learning, and graph models.
- Build real-time and batch pipelines to deliver the models.
- Design indicators to monitor the feature and model performance and conduct continuous model iteration.
- Demonstrate the models to stakeholders in alignment with their expectations.

**Requirements**:

- Bachelor’s or higher degree in Computer Science, Information Technology, Programming & Systems Analysis, Engineering, Statistics, Mathematics or other related disciplines.
- Minimum 3 years’ work experience as a data scientist.
- Strong experience with state-of-the-art machine learning, deep learning, and graph models in fraud detection and risk control system.
- Hands-on experience with feature designing, transformer, and clustering algorithms.
- Excellent analytical skills in big data exploratory analysis and statistical analysis.
- Proficient with Python and Spark/Presto SQL.
- Have strong ownership of projects; self-motivated and can communicate with stakeholders and collaborate with teammates well.
- Experience with identifying fraud/abuse MO on e-commerce platforms and addressing normalization and matching are a plus.
- Experience with automated feature engineering.

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