← Serch more jobs

Statistician, Asset Backed Finance

LinkedIn Barings Charlotte, NC
Not Applicable Posted April 4, 2026 Job link
Thinking about this job
Not Met Priorities
What still needs stronger evidence
Requirements
  • 5+ years of experience in statistical modeling, data analysis, and/or quantitative finance within a financial field, with direct experience in residential mortgages or similar assets a plus.
  • Expert proficiency in statistical analysis software and coding (e.g., R, SAS, Python, MATLAB).
  • Strong knowledge of statistical modeling techniques such as regression analysis, time-series modeling, survival analysis, and machine learning.
  • Proficiency in machine learning algorithms (e.g., random forests, gradient boosting machines, support vector machines, neural networks) and frameworks
  • Experience with data manipulation and visualization tools (e.g., SQL, Tableau, R, Power BI).
  • Proven ability to analyze large, complex datasets and extract meaningful insights that drive strategic decisions.
  • Strong problem-solving skills with the ability to design solutions for modeling complex issues, such as prepayment risk, credit risk, and liquidity risk, using both traditional statistical methods and machine learning techniques.
  • Ability to communicate complex statistical concepts in a clear and concise manner to non-technical stakeholders.
  • Strong collaboration skills and the ability to work cross-functionally with internal teams, including risk, portfolio management, and capital markets.
  • Strong attention to detail and a focus on data integrity.
  • Ability to handle multiple tasks and prioritize effectively in a fast-paced environment.
  • Asset Backed Financing, Data Analysis, Data Science, Machine Learning (ML), Machine Learning Algorithms, Python (Programming Language), SAS Language, Statistical Models, Statistics
Education
  • (Not required) – Master's or Ph.D. degree in Statistics, Mathematics, Engineering, Data Science, or a related field.