- Experience with econometric modeling and statistical analysis.
- Experience with the implementation and creation of various models and algorithms including regression and statistical models. Knowledge of AI or machine learning techniques is desirable.
- Strong programming experience in Java and Python/R. Familiarity with SAS and with tools available in the AWS/Cloud environment. Proficiency in Unix/Linux environment.
- Knowledge of mortgage mathematics is highly desirable. Multifamily analytics and finance knowledge are big plus.
- Experience working with financial data, analytics and cashflows applications.
- Understanding of Credit Risk Model, Conservator Capital Framework (CCF), Credit Risk Transfer (CRT) a plus.
- Understanding agency prepayment models, MBS data, and the MBS market.
- Excellent communication skills, oral and written. Capable of explaining and documenting complex systems.
- Adheres to sound software development and data management practices.
- Conscientious attention to detail, accuracy, and efficiency in analytical work.
- Cross-functional business skills with excellent facilitation and communication skills, strong influencing skills, and ability to effectively present to and work with application team members
- Demonstrated strong analytical and problem-solving skills to conduct analysis independently to address complex economic or business problems.
- Embraces new technologies, enjoys making systems efficient and updating legacy systems.
Preferred Qualifications:
- MS in Computer Science, Statistics, Math, Engineering, or related field, PhD preferred
- 3+ years of relevant experience in building large scale machine learning or deep learning models and/or systems
- 1+ year of experience specifically with deep learning (e.g., CNN, RNN, LSTM)
- Demonstrated skills with Jupyter Notebook, AWS Sagemaker, or Domino Datalab or comparable environments
- Passion for solving complex data problems and generating cross-functional solutions in a fast-paced environment
- Knowledge in Python or C++ / C#, and SQL, object oriented programming, service oriented architectures
- Strong scripting skills with Shell script and SQL
- Strong coding skills and experience with Python (including SciPy, NumPy, and/or PySpark) and/or Scala.
- Knowledge and implementation experience with statistical and machine learning models (regression, classification, clustering, graph models, etc.)
- Hands on experience building models with deep learning frameworks like MXNet, Tensorflow, Keras, Caffe, PyTorch, Theano, or similar
- Experience search architecture (ex - Solr, ElasticSearch)
Key Job functions:
- Develop, implement and test all components using Java/Python/R of financial models, algorithms, cash flow simulations and pricing/risk metrics calculations in end-user or production computing systems for use in business decisions, financial and regulatory reporting, and risk management.
- Use Advanced Analytics and Data Science techniques to efficiently translate complex mathematical, business, and financial modeling logic into software code. Design and execute test cases for modeling and analytical software applications to ensure they meet business needs and model requirements. Design and execute modeling application systems via distributed computing both on premise and on external cloud.
- Monitor emerging technologies and industry best practices of model and analytical system implementation, evaluate and propose adoption of such technologies or best practices.
- Execute model application runs, process/validate model outputs, and produce/review quantitative reports for business use.
- Provide technical guidance or consultation to less senior staff. Serve as technical lead on projects to develop more accurate or refined analytical applications used in pricing, valuation, risk assessment, and the like.
- Communicate complex quantitative analysis in a clear, precise and actionable manner both verbally and in writing.
- Work and collaborate effectively, as part of a team and across organizational lines. Serve as project lead to development and implement solutions to meet business needs.