Data Science - Advisor / SME

• The Finance - Data Science - Advisor role will offer you the flexibility to make each day your own, while working alongside people who care so that you can deliver on the following responsibilities: • Use advanced mathematical, analytical, or econometric tools to create algorithms and analyses that will be used to support the Multifamily CECL and DFAST/forecasting processes within the Finance organization. • Research and evaluate model results and perform credit-related analyses for both 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 and current capabilities, data availability, and alternative uses to drive success of parts of projects, programs, or products. • Ensure application of statistical modeling capabilities from disciplines, such as computer science, computational science and methods, statistics, econometrics, data optimization, and data visualization. • Build predictive analytic capabilities within the team 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 to support risk measurement, financial valuation, decision making, and business performance for parts of products or initiatives. • Ensure the team communicates complex ideas and solutions effectively to business partners through data visualizations, technical documentation, and non-technical presentation materials. Minimum Required Experiences Total 10 years and 6 years in Data Science Desired Experiences Bachelor degree or equivalent A Master's degree or equivalent in Data Science, Applied Economics, Statistics, or other similar graduate studies • Familiarity with advanced techniques including machine learning and natural language processing (NLP) • Prior quantitative and finance training, including forecasting/stress testing (DFAST) knowledge. • Ability to direct and evaluate the more technical aspects of data analysis and research, while also managing team in a timely manner to focus on the broader context and key impacts of the analysis • Ability to build and maintain strong business relationships with partners • Strong written and verbal communication skills • Relationship management including managing and engaging stakeholders, partners, customers, and building relationship networks • Strong analytical and problem-solving skills to conduct and manage analysis to address complex business problems • Programming including coding, debugging, and using relevant languages such as Python, R, SQL, or similar • Experience in the process of analyzing data to identify trends or relationships to generate business insights and inform conclusions about the data • Expertise in visualizing data to identify, summarize and explain observed data patterns