Risk modelling analyst
3 weeks ago
Sea Money is a part of Sea Group, a leading global consumer internet company. Sea Money’s mission is to better the lives of individuals and businesses in our region with financial services through technology. Sea Money’s offerings include mobile wallet services, payment processing, credit offerings, and related digital financial services and products. These are available in seven markets across Southeast Asia and Taiwan under various brands, including Shopee Pay, SPay Later, and other brands.
Job Description:Work on risk model development for retail and SME finance products such as consumer lending, personal finance, small and medium-sized enterprises loan and so on
Build models and tools for credit and fraud risk identification in various aspects. For example, credit risk modelling, income estimation, customer information verification, anti cash-out, non-starter detection, account take over and so on
Analyse and conduct feature engineering for massive data such as customer profiling, e-commerce transaction, and so on and deploy the feature pipeline
Using graph mining, time series data modelling, graph & item embedding techniques to extract information from raw data
Collaborate closely with the risk policy and business team. Translate business need and insight into machine learning models
Research model methodology and data mining techniques to improve model performance
Requirements:Bachelor's degree in Machine Learning, Business Analytics, Information Technology, Finance, Economics, Statistics, Mathematics, or a related field. Master's and Ph D degree are preferred.
1-5 years relevant credit or anti-fraud model development experience
Experienced with data mining and feature engineering from massive raw data especially the alternative credit data
Solid understanding and hands on experience of machine learning models such as boosting trees, regression models and good sense in feature engineering
Good coding skill using SQL, Spark and Python
Eager to learn new things and has passion in work
Take responsibility, team oriented, result oriented, customer oriented and self driven
Experience in network analysis, search and recommendation system and other machine learning field is a plus#J-18808-Ljbffr
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