基本条件:本科以上学历,会英文懂代码,愿意在广州发展的童鞋们。
有意者请发简历到alax_hou@163.com,详情咨询内部回复或邮件,来邮件请注明申请职位哦。
补充一下工作地点: 广州太古汇
<非诚勿扰>
Requirements:
- Hold a Bachelor above degree in Computer Science, Mathematics, Statistics, Operation Research, Engineering or other highly quantitative / technical majors. (Master or PhD is preferred);
- Proficient in SAS (covering base SAS, SAS STAT, Enterprise Miner) or other leading statistical software required;
- Comfortable with mining massive volume of data for quick insight discovery; detailed oriented, conscious of stringent quality control and able to work under pressure to meet tight deadlines;
- A highly analytical and logical individual who is independent, self-motivated and a team player;
- Good communication skills in verbal and written English;
- Prior experience in advanced data mining and/or financial services industry a plus
Job Duties:
- Collect and comprehend business requirements when andwhere advanced data mining solution is demanded;
Extract / collect, analyze, interpret and present highlyquantitative yet relevant information under proper business context;
- Flexibly and innovatively apply diverse quantitativemethods including (but not limited to) association, decision tree, clustering,multi-variate regression, time series trending, to design and develop robust,relevant data mining solutions - descriptive or predictive;
- Independently and proficiently execute all stepsrelating to Modelling, incl. target definition, sampling, variable selection/transformation/ imputation, dimension reduction, model development /selection,validation & scoring;
- Deliver complete set of quality model outputs in atimely manner, articulate technical details, and support all model-relatedinquiries to enable model application;
- Develop closed-loop mechanism in model application withproper test/control set up to enable back-end performance validation;
- Proactively identify and support automationopportunities to shorten turnaround, hence contribute to increased of outputs,including: a) automation in model data extraction, summarization and derivation;b) automation of monthly scoring and KPI monitoring; c) automation in modelevaluation


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