Conduct in-depth industry research utilizing a combination of external and internal research sources and data sets. This research will be specifically tailored to provide a comprehensive credit view of various industries, enabling the organization to make informed credit risk assessments and strategic decisions.
Lead thematic and portfolio research initiatives focused on identifying and analyzing emerging risk trends. This involves synthesizing data and insights to understand how these trends impact industry dynamics and credit risk, thereby informing the development of proactive risk management strategies.
Develop and refine industry models designed to project financial outcomes based on macroeconomic indicators. These models will be instrumental in forecasting industry performance and assessing potential credit risks, allowing for more accurate and forward-looking credit evaluations.
Utilize Python and SQL skills to efficiently manage and manipulate large data sets. This includes performing back testing and conducting detailed portfolio analytics to validate models and ensure the robustness of credit risk assessments (Optional).
Apply Large Language Model (LLM) skills to synthesize information from multiple sources, generating systematic and comprehensive reports. This capability will enhance the ability to integrate diverse data points and insights into cohesive analyses that support strategic decision-making.
Collaborate with cross-functional teams to integrate industry research findings into broader credit risk management processes. This includes working with stakeholders to develop tools and frameworks that enhance the organization's ability to manage credit risk effectively.
Present research findings and analytical insights in a clear and detailed manner to senior management and other stakeholders, ensuring that the implications for credit risk are well understood and actionable.
Continuously monitor and evaluate industry developments and macroeconomic trends, updating models and research outputs as necessary to reflect the latest insights and maintain the relevance and accuracy of credit risk assessments.
Required Qualifications, Skills, and Capabilities:
Bachelor’s or Master’s degree in Mathematics, Statistics, Finance, or related fields.
3+ years of relevant work experience in Financial Risk Analytics or Wholesale Credit Risk management.
Excellent problem-solving, communication, and teamwork skills.
Desire to use modern technologies as a disruptive influence within banking.
Attentive to detail and easily adaptable.
Enthusiastic about knowledge sharing and collaboration.
Strong interpersonal skills – you listen and communicate in a direct, succinct manner.
Proven ability to develop collaborative relationships with key internal partners to achieve objectives and prioritizations.
Experience with analytics and data tools (e.g., Python/Anaconda, R, TensorFlow, Keras/PyTorch, Spark, SQL) (Optional).
Additional Skills, Experience, and Qualifications:
Experience in quantitative modeling using Python.
Experience in publishing industry research articles.
