Senior Data Scientist

Overall Purpose of the Role:

As a Senior Data Scientist, you will play a pivotal role in assessing, analyzing, and mitigating risks within our company where Merchant Cash Advances (MCA’s) are offered to small and medium enterprises (SME) merchants. You will be responsible for overseeing and completing the full model development cycle, from extracting data up to presenting findings to relevant stakeholders. This position requires a keen understanding of data and modelling standards and principles, credit scoring principles and machine learning techniques.

Experience and Skills Required:

• Monitor the performance of SME portfolios, identifying trends and potential risks, and recommending appropriate risk mitigation strategies.

• Managing the strategic direction of the portfolio by balancing both risk and sales objectives
• Oversee and take part in the development and maintenance of risk models and methodologies to quantify and manage credit risk exposure.
• Building scorecards and other credit risk models within the credit lifecycle.
• Collaborate with cross-functional teams including finance, operations, and compliance to ensure alignment with risk management objectives.
• Prepare and present reports to senior management, highlighting key risk metrics, trends, and recommendations.
• Develop stress testing scenarios and sensitivity analyses to assess the resilience of the SME portfolio under various economic conditions.
• Stay updated on changes to regulatory frameworks,
particularly IFRS9 requirements, and ensure compliance in credit risk management practices and reporting.
• Provide guidance and mentorship to team members, fostering a culture of continuous learning and development within the team.

Qualification/s:

• Degree in mathematics, statistics, data science, or a related quantitative field.
• At least 5 years of experience in credit data science within retail, insurance or financial
services.
• Strong understanding of credit risk models and advances in machine learning techniques that could be applied in the field of credit scoring.
• Strong understanding of IFRS9 principles and their application to credit risk management, including Expected Credit Loss (ECL) calculations and impairment assessment methodologies.
• Strong analytical skills with the ability to interpret complex financial and trade data and make informed decisions.
• Excellent communication and presentation skills, with the ability to convey complex concepts to non-technical stakeholders.
• Proven leadership abilities with experience in guiding and mentoring junior team members.
• Ability to thrive in a fast-paced, dynamic environment and manage multiple priorities effectively.
• Familiarity with SME lending practices and challenges, including industry-specific risk
factors, is highly desirable.
• Proficiency in software tools such as Databricks, SQL, R, or Python