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Job Description :

• Responsible for the construction of various risk scoring models, establishing credit business credit scoring models, customer credit models and other data models
• Responsible for the design, development and implementation of the model, including not limited to applying for score cards, anti-fraud scores, and collection score cards.
• Analyzes complex business problems using data from internal and external sources to discover
• Provides actionable insight to decision-makers to influence strategy and performance
• Processing, cleansing and verifying the integrity of structured and unstructured data for analysis
• Doing ad-hoc analysis and pretending and presenting results in clean manner
• Control, maintain, and improve high level of data quality
• Generates forecast, recommendations, and strategic/tactical plans to drive actions
• Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
• Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.
• Assess the effectiveness and accuracy of new data sources and data gathering techniques.
• Develop custom data models and algorithms to apply to data sets.
• Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
• Develop company A/B testing framework and test model quality.
• Coordinate with different functional teams to implement models and monitor outcomes.
• Develop processes and tools to monitor and analyze model performance and data accuracy.

Requirements :

• At least 3 years of working experience
• Strong presentation skills and ability to communicate complex findings and ideas in plain language
• Strong problem solving skills with an emphasis on product development.
• Experience working with and creating data architectures.
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
• Excellent written and verbal communication skills for coordinating across teams.
• A drive to learn and master new technologies and techniques.
• Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
• Experience querying databases and using statistical computer languages: R, Python, SQL, etc.
• Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
• Experience analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, Facebook Insights, etc.
• Having Knowledge Big Data tools with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.  
• Experience visualizing/presenting data for stakeholders using: Periscope, Business Objects, D3, ggplot, etc.
• Familiar with at least one programming language such as Phyton, Java, JavaScript
• Excellent written and verbal communication skills
• Ability to multitask
• Ability to communicate with clarity compassion
• Able to work independently and in a team
• Exposed in Contributing to the quality strategy of the products is a ++