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Data Scientist

  • Anywhere

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 ++