Model Risk Analyst, Upgrade

• Advanced Degree (MS/PhD) in Statistics, Mathematics, Data Sciences or a related quantitative discipline
• 0-2 years experience as a Data Scientist, Statistician, or related modeling background. Recently graduated students welcome to apply
• Experience and/or strong interest in latest machine learning techniques (Random Forest, Gradient Boosted Trees, etc.) strongly preferred
• Ability to go deep into complex technical topics, understand modeling and algorithms
• Proficient in Python
• Ability to write documentation and present analysis to people with different levels of expertise (e.g., technical staff, business leads, etc.)
• Detail oriented and strong analytical skill set
• Proactive, driven, and ability to work in a fast-paced environment

Desirable

• Upgrade’s Model Risk Management team plays a critical role in ensuring the integrity and reliability of the machine learning/statistical models used across the company. As a part of Upgrade’s risk function, we provide effective and independent challenges to assess, validate, and mitigate risks related to model development and usage, ensuring they align with regulatory standards and best practices
• As a Model Risk Analyst, you will be integral in identifying model risks and strengthening model robustness and performance
• Reporting to Upgrade’s Director of Model Risk Management, this role will:
• Review and validate statistical/machine learning models for various business areas, including Credit Risk, Fraud, Marketing, and Operations
• Review and challenge model methodology, data process, outcome analysis to identify gaps and improve on model performance
• Actively research new tools and techniques available for model development and validation
• Collaborate with various teams across Upgrade in model validation process: Decision Science, Credit Risk, etc