Remote - Quantitative Analyst

Bachelor's degree with a foundation in quantitative and analytical skills, preferably in fields such as Applied Mathematics, Physics, Engineering (preferably in Statistical, Aerospace, Finance), Statistics, Capital Markets or Corporate Finance. Experience in quantitative research roles, especially across Capital Markets, Investment Management, and Trading. Hands-on experience in building and validating statistical, econometric, or predictive models. Proficient in handling large data sets, working with simulation models, and utilizing forecasting tools. A background in research-driven environments that focus on statistical theory, model design, and analytical experimentation. Strong analytical reasoning paired with structured problem-solving skills. Experience with correlative regression and theoretical regression techniques. A critical thinker who pays close attention to detail and numerical accuracy. High learning agility along with the ability to independently direct technical research. Excellent communication skills in English, both written and verbal. Comfortable working in a high-energy, fast-paced environment. Well-versed in Python, R, VBA for Excel automation, and MATLAB. Proficient in Monte Carlo simulations, time-series analysis, as well as correlational and multivariate regression techniques, along with statistical hypothesis testing and forecasting. Able to compare, optimize, and validate various model types. Possesses a strong grasp of processes and theoretical foundations.

Design, create, and maintain statistical and quantitative models that improve lending strategies, risk management, pricing, and portfolio approaches. Perform comprehensive statistical research to uncover valuable insights into borrower behavior, credit performance, prepayment risk, default risk, and trends in loss severity. Develop, test, and validate predictive models by leveraging historical data related to loans, collateral, market dynamics, and macroeconomic conditions to strengthen our underwriting and risk-rating systems. Utilize Monte Carlo simulations, time-series analysis, and regression modeling for projection across various economic and stress scenarios. Assess, contrast, and enhance different model structures and methodologies. Develop automated analytical tools, dashboards, and model outputs using Python, R, MATLAB, and Excel/VBA to boost efficiency and scalability. Lead research projects, steering them from hypothesis development through experimentation, validation, documentation, and presentation of findings. Maintain high standards of numerical accuracy, methodological integrity, and thorough documentation to support internal governance, audits, and regulatory compliance. Stay updated on the latest advancements in quantitative finance, statistical modeling, and analytical techniques to continually enhance WBL’s modeling and forecasting abilities. Foster a vibrant, data-driven culture by proactively seeking ways to elevate decision-making through insightful quantitative analysis.