Job Summary 

The Data Scientist is responsible for advanced analytics on data, usually associated with data mining or statistical analysis. This often involves assembling and preparing forecasting, response modeling, fraud detection, segmentation, and CRM. Industry specific methods and solutions are used to solve industry specific tasks.

Key Responsibilities  

• Clarify the business problem for the purpose of data analysis.
• Define data mining application requirements.
• Define, build, and verify analytical models.
• Interpret and document the analytical models and results.
• Support clients in scoring analytical models or score models on behalf of the client.
• Deliver a workshop or a presentation to clients on lessons learned from the analysis and model development.
• Train clients on any techniques required for their future use of analytical models.

Work Environment

Flexible to work in office or customer site and to travel across East China when required

Basic Qualifications     

• Bachelors Degree or above in Math, Statistics, Computer Science, Finance, Business, Finance, etc.
• 1-3  years or above analytic modeling  experience including at least 2 years continuous experience in relevant industries or business
• Should have a strong analytic background, typically in mathematics and the application of statistics
• Have ability to develop both descriptive and predictive analyses using techniques such as linear regression, logistic regression, decision tress, clustering, and others.
• Familiar with SQL and good knowledge of analytical toolsets (SAS/Python/R/Spark, etc).
• Knowledge of the industry associated with the project.
• Can work independently and under hard pressure.
• Learn fast and high interest of pursuing a consulting career
• Good communication, presentation and writing skills

Preferred Qualifications

• Familiar with Banking business and Banking application
• Familiar with data visualization tools such as Tabulae, PowerBI, etc
• Familiar with analytic tools (Scikit-Learn/XGBoost/LightGBM/TensorFlow/Keras/Pytorch/Spark etc)
• Mastering common Machine learning/Deep learning algorithms
• Management experience will be a plus