Credit Risk Modeling Specialist Job Vacancy in Mzuzu, Malawi – Banking & Finance

Job Description

Position: Credit Risk Modeling Specialist

Company: Standard Bank Malawi

Location: Mzuzu, Malawi

Experience: 5+ years in credit risk modeling, preferably in banking sector

Education: Bachelor’s degree in Finance, Economics, Statistics or related field; Master’s preferred

Employment Type: Full-time

Industry: Banking & Finance

Department: Credit Risk Management

Salary: SSP 1,200,000 – 1,800,000 per annum

Vacancies:1

Company Overview

Standard Bank Malawi is a leading financial institution delivering innovative banking solutions across the country. With a strong heritage dating back over a century, the bank operates in major cities including Lilongwe, Blantyre, and Mzuzu, supporting both corporate and retail clients. As part of the Standard Bank Group, it leverages global expertise while maintaining a deep commitment to local economic development. The bank’s focus on digital transformation, sustainable finance, and inclusive growth makes it a top employer for professionals seeking dynamic career opportunities in Malawi. This role contributes directly to the bank’s mission of fostering financial stability and supporting the growth of businesses throughout the region.

Job Overview

The Credit Risk Modeling Specialist will lead the design, development, and validation of advanced credit risk models that underpin the bank’s lending decisions, portfolio monitoring, and regulatory reporting. Working within the Credit Risk Management department, the specialist will collaborate with data scientists, business analysts, and senior management to ensure models are robust, compliant, and aligned with the bank’s strategic objectives. This position offers a unique opportunity to influence risk policy, enhance predictive analytics, and drive data‑driven decision making across the organization. For more information about the bank’s career portal, visit https://malawijobsearch.com.

Key Responsibilities

• Develop, calibrate, and validate credit scoring and probability of default (PD) models using statistical and machine‑learning techniques.
• Perform back‑testing, stress testing, and model performance monitoring to ensure ongoing accuracy.
• Collaborate with the data engineering team to acquire, clean, and transform large datasets from multiple sources.
• Prepare comprehensive model documentation, validation reports, and regulatory submissions in line with Basel III and local banking regulations.
• Provide analytical support to credit committees, presenting model insights and risk assessments to senior stakeholders.
• Mentor junior analysts on modeling best practices and promote a culture of continuous improvement.

Required Skills

• Proficiency in statistical software such as R, Python, SAS, or MATLAB.
• Strong understanding of credit risk concepts, Basel III, and local regulatory frameworks.
• Experience with data manipulation, SQL, and big‑data platforms (e.g., Hadoop, Spark).
• Excellent analytical, problem‑solving, and communication skills.
• Ability to translate complex model outcomes into actionable business recommendations.
• Attention to detail and a commitment to model governance and auditability.

Education

A minimum of a bachelor’s degree in Finance, Economics, Statistics, Mathematics, or a related quantitative discipline is required. Candidates holding a master’s degree or professional certifications such as FRM, CFA, or PRM are highly preferred, reflecting the advanced analytical nature of the role.

Experience

Applicants must have at least five years of hands‑on experience developing and validating credit risk models within a banking or financial services environment. Prior exposure to regulatory model validation, portfolio risk analytics, and cross‑functional project delivery will be considered a strong advantage.

Salary

The compensation package ranges from SSP 1,200,000 to SSP 1,800,000 annually, commensurate with experience, qualifications, and demonstrated expertise. The package includes performance‑based bonuses, health insurance, pension contributions, and other statutory benefits.

Benefits

• Competitive base salary with annual performance bonus.
• Comprehensive medical and dental coverage for employee and dependents.
• Retirement savings plan with employer matching contributions.
• Paid annual leave, sick leave, and maternity/paternity leave in line with Malawian labor law.
• Employee assistance program and wellness initiatives.
• Opportunities for international secondments within the Standard Bank Group.

Training

• Access to Standard Bank Academy for continuous professional development.
• Sponsored certifications in risk management, data science, and financial modeling.
• Regular workshops on emerging technologies such as AI, machine learning, and advanced analytics.
• Mentorship programs pairing new hires with senior risk leaders.

Working Environment

Based in the modern Mzuzu office, the specialist will work in a collaborative, technology‑enabled environment that encourages innovation and knowledge sharing. The bank promotes a flexible work arrangement, allowing a blend of on‑site and remote work to support work‑life balance while maintaining high standards of data security and confidentiality.

Application Process

Interested candidates should submit their updated CV and a cover letter outlining their relevant experience through the online portal. Applications will be reviewed on a rolling basis, and shortlisted candidates will be invited for a virtual interview followed by an on‑site assessment. For additional guidance on the application steps, please refer to https://www.ghanajobsearch.com/.

Equal Opportunity Statement

Standard Bank Malawi is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive workplace where all employees are valued, respected, and given the chance to thrive regardless of gender, race, religion, disability, or any other protected characteristic. Our recruitment practices are designed to ensure fairness and transparency, supporting the broader goal of equitable employment in Malawi.