Description:

Lead the assessment, analysis, and mitigation of credit risks within the MCA Credit Analytics team at GoTyme.
Oversee the full model development cycle, from data extraction to presenting findings to stakeholders.
Improve credit decisioning and portfolio performance for Merchant Cash Advance products using data and machine learning techniques.
Ensure models are governed, validated, deployed, monitored, and reviewed throughout their lifecycle.

Requirements:

Degree in Data Science, Statistics, Mathematics, or a related quantitative field.
At least 5 years of experience in credit data science or credit analytics within a bank, fintech, lender, or consulting environment.
Strong background in statistical modelling, machine learning, and predictive analytics, particularly in credit risk models.
Proficiency in Python and/or SQL, with experience in building and validating credit risk models.
Familiarity with BSP credit risk guidelines and IFRS 9 is advantageous.

Opportunity to provide guidance and mentorship to junior team members.
Contribute to the strategic direction of the portfolio and enhance portfolio monitoring tools and dashboards.

Skills