Staff Data Scientist, Block

• Bachelor's degree in the physics, economics, statistics, or a similar STEM field with 8+ years of related work experience; Graduate degree w/ 5+ years of relevant working experience; or 9+ years of relevant working experience
• Knowledge of data science modeling techniques, methodologies (e.g. familiarity with deep learning, boosted trees, and unsupervised learning)
• Experience with scripting and data analysis programming languages, such as Python (preferable) or R
• Advanced proficiency with SQL and data visualization tools (e.g. Tableau)
• Quantitative skills with the ability to interpret complex data sets
• Excellent communication skills with the ability to present technical information clearly and concisely

Desirable

• We are looking for a Staff Data Scientist with model validation experience to join our team and support our model risk management activities
• Your responsibilities will include validating machine learning models as applied to regulatory compliance such as anti-money laundering (AML), Know Your Customer (KYC), and sanctions screening. You will also provide analytical support and insights to improve our model development, and documentation standards
• You should have strong quantitative skills, attention to detail and knowledge of relevant regulations and industry best practices. You will be fully remote and report into our Foundational Model Risk Management Lead
• Validate machine learning models using data analysis, testing procedures and quality assurance methods
• Evaluate and improve model validation activities, processes, and metrics
• Assess and advise on model governance frameworks, and development practices
• Identify model risks, issues, and gaps to management
• Provide analytical support and insights to improve model development, validation, and documentation standards
• Stay updated on latest trends, developments and best practices in machine learning and compliance risk management
• Maintain validation documentation following internal policies
• Develop monitoring dashboards for ongoing model performance monitoring (e.g. model drift)
• Coordinate with business partners, Data Science, Product, Engineering & Technology
• Develop partner relationships and have a understanding of the businesses