Job Summary:

The Finance - Data Science - Advisor role will provide flexibility while working alongside cross-functional teams to support Multifamily CECL and DFAST/forecasting processes within the Finance organization. The role will leverage advanced mathematical, analytical, econometric, and statistical modeling techniques to develop algorithms, predictive analytics, and insights that support risk measurement, financial valuation, decision-making, and business performance.

Key Responsibilities:

• Use advanced mathematical, analytical, or econometric tools to create algorithms and analyses supporting Multifamily CECL and DFAST/forecasting processes.
• Research and evaluate model results and perform credit-related analyses for expected and stress scenarios, including

CECL/DFAST.

• Coordinate team activities with product and/or business owners, data engineers, and platform teams to understand business needs, current capabilities, data availability, and alternative uses.
• Apply statistical modeling capabilities across disciplines including computer science, computational science and methods, statistics, econometrics, data optimization, and data visualization.
• Build predictive analytic capabilities to enhance the delivery of business applications and support the integration of data and statistical models or algorithms.
• Apply innovative industry practices in research and testing to product development, deployment, and maintenance.
• Oversee the design and build of new modeling applications supporting risk measurement, financial valuation, decision-making, and business performance.
• Communicate complex ideas and solutions effectively to business partners through data visualizations, technical documentation, and non-technical presentation materials.

Required Qualifications:

• 6+ years of relevant experience.
• Strong programming experience, including coding and debugging using languages such as Python, R, SQL, or similar.
• Strong analytical and problem-solving skills to conduct and manage analysis addressing complex business problems.
• Experience analyzing data to identify trends or relationships and generate business insights.
• Expertise in visualizing data to identify, summarize, and explain observed data patterns.
• Ability to direct and evaluate technical aspects of data analysis and research while maintaining focus on broader business impacts.
• Strong written and verbal communication skills.
• Ability to build and maintain strong business relationships with business partners and stakeholders.

Preferred Qualifications:

• Bachelor's degree or equivalent.
• Master's degree or equivalent in Data Science, Applied Economics, Statistics, or a similar graduate field.
• Familiarity with advanced techniques including machine learning and natural language processing (NLP).
• Prior quantitative and finance training, including forecasting and stress testing (DFAST) knowledge.
• Experience managing and engaging stakeholders, partners, customers, and relationship networks.
• Experience with R programming, Tableau, Python, SQL, DBeaver SQL client software, and BitBucket.