Data Scientist
The Role
As the key contributor in our data-driven lending business, you will be responsible for supporting our risk management, operations, capital markets, and marketing functions with insights gained from data-mining internal and external data. The ideal candidate is adept at using large data sets to find opportunities for risk management and process optimization, and at using models to test the effectiveness of different consumer lending strategies. Candidates must have strong experience using a variety of data mining and data analysis methods; using a variety of data tools; building and implementing models; using and creating algorithms; and creating and running simulations.
Responsibilities
· Mine and analyze data from internal and external sources to drive optimization and improvement of lending strategies
· Assess the effectiveness and accuracy of new data sources and data gathering techniques
· Develop customized models and algorithms to apply to the company's underwriting, fraud detection, operations, and marketing functions
· Use predictive modeling to increase and optimize acquisition, underwriting, customer experience, 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
Must Have Skills
· Innate curiosity combined with strong learning capability
· Problem solving skills with an emphasis on product development
· Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages and drawbacks
· Expertise in advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and applications
· Experience using statistical computer languages (SAS or R, Python, SQL, etc.) to manipulate data and draw insights from large data sets
· Ability to liaise cross functionally with excellent written and verbal communication skills
Nice to Have Skills
· Experience in consumer lending, fraud analytics, or database marketing
· Experience with distributed data/computing tools eg Map/Reduce, Hadoop, Hive, and Spark
Qualifications
· Masters or PhD degree in Statistics, Computer Science, Mathematics, Social Science, Engineering, or other related Quantitative discipline
