Data Scientist, Upgrade

• Advanced Degree (MS/PhD) in Data Science, Statistics, Mathematics, Computer Science, Finance, or a related quantitative discipline
• 2 years of hands-on experience in a data science or analytics role, preferably in financial services
• Experience and/or strong interest in machine learning techniques (Random Forest, Gradient Boosted Trees, etc.) strongly preferred
• Strong proficiency in Python (Pandas, Numpy, Scikit-learn) and SQL
• Ability to write documentation and present analysis to people with different levels of expertise (e.g., technical staff, business leads, etc.)
• Proactive, driven, and ability to work in a fast paced environment

Desirable

• Build and maintain credit and fraud policy simulators used to ensure properly functioning systems and identify risk decisioning enhancements
• Build and deploy statistical models and machine learning algorithms to solve business problems in areas like credit risk, fraud detection, pricing, customer segmentation, and marketing attribution
• Validate models to identify factors that may affect model performance
• Analyze large, structured and unstructured datasets using SQL, Python or similar tools
• Stay up to date with the latest trends and technologies in data science and fintech, actively research new tools and techniques available for model development
• Collaborate with cross-functional teams including risk, marketing, product, and engineering to define data-driven strategies