Financial Credit Risk Analyst

Slate Systems Lab is seeking a Financial Credit Risk Analyst to develop and enhance credit risk models and analytical frameworks. The role requires expertise in coding, particularly in Python, and involves analyzing borrower and portfolio risk, performing statistical analysis, and collaborating with financial institutions. This position is ideal for analytical professionals interested in translating complex datasets into actionable insights, contributing to innovative risk solutions in emerging markets.
Financial Credit Risk Analyst
Slate Systems Lab
Full-time | Remote-Friendly
Important Hiring Requirement for this role*


This is a coding-intensive analytical role.


Applicants should be conversant with:



Building an appropriate financial or quantitative model; and
Implementing that model in Python.

Candidates who are only able to produce spreadsheet-based models or conceptual frameworks, without translating them into working Python code, will not be considered for this position.
About Slate Systems Lab
Slate Systems Lab is building next-generation environmental intelligence infrastructure for financial institutions, enterprises, and public-sector stakeholders across emerging markets.
We combine advanced data systems, risk analytics, and environmental intelligence to help organizations better understand and manage exposure to environmental and climate-related risks.


As we expand our financial risk capabilities, we are looking for a Financial Credit Risk Analyst to help bridge environmental intelligence and financial decision-making.


The Opportunity
We are seeking a highly analytical professional with experience in credit risk, portfolio risk, or financial risk modeling.
In this role, you will contribute to the development of risk methodologies that help financial institutions better understand how external risk factors influence borrower performance, portfolio resilience, and lending decisions.


You will work at the intersection of finance, data, and risk analytics while collaborating with internal teams, external partners, and financial institutions.


This role is ideal for someone who enjoys translating complex datasets into actionable risk insights and wants to contribute to innovative risk solutions in rapidly evolving markets.


Key Responsibilities
Credit Risk Analysis & Modeling
· Support the design, development, and enhancement of credit risk models and analytical frameworks.


· Analyze borrower, portfolio, and sector-level risk drivers.


· Contribute to methodologies used for estimating and assessing credit risk metrics.


· Perform statistical analysis and model validation exercises.


· Assist in developing risk scoring methodologies and analytical outputs for institutional users.


Portfolio & Risk Intelligence


· Analyze portfolio-level exposures and emerging risk trends.


· Support scenario analysis, sensitivity analysis, and stress-testing exercises.


· Develop analytical insights that help organizations understand risk concentration and portfolio resilience.


· Contribute to the creation of risk reporting frameworks and client-facing analytical outputs.


Stakeholder Engagement
· Collaborate with financial institutions, risk teams, analysts, and technical stakeholders.
· Gather business requirements and understand how risk information is used within lending and portfolio management processes.


· Present analytical findings and model outputs to both technical and non-technical audiences.


· Support pilot projects, validation exercises, and ongoing client engagements.


Research & Innovation


· Stay informed on developments in credit risk, climate risk, environmental risk, financial regulation, and emerging analytical methodologies.


· Evaluate new datasets, modeling techniques, and analytical approaches that can strengthen risk assessment capabilities.


Contribute to continuous improvement of internal analytical frameworks and methodologies.


Important Hiring Requirement
This is a coding-intensive analytical role.
Applicants should be conversant with:



Building an appropriate financial or quantitative model; and
Implementing that model in Python.

Candidates who are only able to produce spreadsheet-based models or conceptual frameworks, without translating them into working Python code, will not be considered for this position.
Qualifications Required
· Bachelor's degree in Finance, Economics, Statistics, Mathematics, Actuarial Science, Data Science, Risk Management, or a related field.
· Experience in credit risk analysis, portfolio risk management, risk modeling, banking, financial services, consulting, or related fields.


· Strong understanding of key credit risk concepts, including: PD, LGD, EL, Portfolio Risk, Risk Rating Methodologies


· Experience working with structured datasets and quantitative analysis.


· Proficiency in Python, SQL, R, or similar analytical tools.


· Strong proficiency in Python for quantitative analysis.


· Experience with libraries such as Pan