Data Science - Washington DC - Fulltime

Job Description

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. Desired Experiences
Bachelor degree or equivalent
A Masters 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
Tools
R programming
Tableau
Python
SQL
DBeaver SQL client software
BitBucket