Data Scientist (Credit Analytics)

GoTyme Bank; Johannesburg; On-site; ZAR 700,000 - 1,200,000; Full time

Benefits offered by this job

Life Cover

Health Insurance

Retirement Annuity

Access to company shares

Wellness days

Job summary

GoTyme Bank Corporation is seeking a Data Scientist in South Africa to assess and mitigate credit risk for MCA SA. You will build and monitor scorecards, features, and provisioning models, and partner with data engineers to productionize analytics.

You will analyse customer and business health data to identify drivers of risk, support portfolio analytics, and collaborate across teams to embed data-driven decisions in underwriting and product strategy.

Qualifications

• Degree in Data Science, Statistics, Mathematics, or related quantitative field.
• 3+ years of experience in data science, credit analytics, or credit risk management within a bank, fintech, lender, or consulting environment.
• Strong background in statistical modelling, machine learning, and predictive analytics.
• Proficiency in Python and SQL; experience building and validating credit risk models.

Responsibilities

• Develop, implement, and maintain acquisition scorecards and models to evaluate MCA applicants.
• Build and iterate credit risk features and model inputs with engineering and modellers.
• Monitor models and analytics dashboards for drift, performance, and data quality.
• Design experiments for policy changes and assess impact on risk and portfolio performance.
• Collaborate with product, finance, and operations to embed data-driven decisions.

Skills

Statistical modelling

Machine learning

Predictive analytics

Communication

Cross-functional collaboration

Education

Degree in Data Science/Statistics/Mathematics

Tools

Python

SQL

Job description

The Data Scientist will play a pivotal role in assessing, analysing, and mitigating credit risks within the MCA SA Credit Analytics team at GoTyme. Working end-to-end from data exploration through to production-aligned features and monitoring, the candidate will use data, feature engineering, and experimentation to improve credit decisioning and portfolio performance for the Merchant Cash Advance product.

Credit Risk Modelling

• Develop, implement, and maintain acquisition scorecards and models to evaluate MCA applicants
• Build and iterate credit risk features and model inputs (behavioural signals, affordability proxies, stability-tested transformations), partnering closely with senior modellers and engineering
• Contribute to the development and improvement of predictive models using modern machine learning approaches, with a focus on robustness, stability, and deployability
• Monitor provision models aligned with regulatory and accounting standards
• Enhance portfolio monitoring tools and dashboards to track credit performance and early warning signals, including drift, stability, segment performance, and data quality checks

Data Analysis & Insights

• Analyse customer, transactional, repayment, and business health data to identify drivers of risk, loss, approval rates, and customer outcomes
• Identify trends, correlations, and anomalies that impact take up rate, credit performance and portfolio stability
• Support portfolio analytics: vintage analysis, roll-rates, migration, early warning indicators, collections funnel analytics, and loss driver deep-dives
• Collaborate with product, finance, and operations teams to embed data-driven decision-making

Credit Policy & Experimentation

• Design, run, and evaluate credit policy experiments (cut-offs, limits, pricing/risk trade-offs, segment strategies), including post-implementation reviews
• Develop segmentation and behavioural models to drive proactive portfolio management
• Support stress testing and scenario analysis

Innovation & Automation

• Design and deploy machine learning models for predictive credit risk assessment
• Leverage advanced analytics to streamline underwriting and risk monitoring processes
• Continuously explore new data sources and analytical methods to improve risk evaluation
• Work with Data/Engineering to improve data definitions, quality, lineage, and reproducible pipelines; document feature logic and assumptions

Governance & Documentation

• Contribute to governance documentation including model inputs, feature catalogues, monitoring evidence, and change logs.
• Ensure all modelling work meets internal standards and applicable regulatory requirements

Requirements

• Degree in Data Science, Statistics, Mathematics, or a related quantitative field
• 3+ years of experience in data science, credit analytics, or credit risk management within a bank, fintech, lender, or consulting environment

Essential

• Strong background in statistical modelling, machine learning, and predictive analytics
• Proficiency in Python and/or SQL
• Experience building and validating credit risk models, including scorecards and provisioning models
• Solid grounding in predictive model evaluation - ranking performance, calibration, and stability - and business impact measurement
• Exposure to advanced machine learning concepts (ensemble methods, cross-validation, hyperparameter tuning) and the ability to apply them responsibly in production settings
• Strong business acumen with the ability to communicate insights to both technical and non-technical stakeholders
• Curious and pragmatic, focused on measurable outcomes; comfortable working in detail and iterating quickly while maintaining quality
• Collaborative and able to work across markets and time zones

Desirable

• Experience in SME lending, merchant cash advances, or alternative credit products
• Familiarity with IFRS 9, Basel, or equivalent credit risk regulatory frameworks
• Experience with bureau data, open banking/transactional data, device/behavioural signals, or alternative data sources
• Exposure to cloud-based data platforms (Databricks, BigQuery, Snowflake, AWS, GCP, or Azure) and version control (Git/Bitbucket)
• Familiarity with model monitoring, governance, and documentation practices in regulated environments

Benefits

Our Benefits Include:

Comprehensive Group Life Cover

• Life Cover
• Funeral Cover
• Global Education Protector
• Disability Cover (incl. Contribution Protector)
• Severe Illness Benefit

Healthcare That Works for You

• Full company contribution to Health Insurance for eligible employees
• Partial company contribution to Medical Aid (Key Health or Discovery) options for eligible employees

Plan for Your Future

• Access to a Retirement Annuity, with convenient payroll deductions to help you save for retirement while benefiting from applicable tax advantages

Other benefits include:

• EAP support (counselling, financial and legal for you and anyone financially dependent on you).
• Competitive, industry-benchmarked salaries.
• Non-guaranteed performance bonuses.
• Access to company shares (T's & C's apply).
• Wellness days.
• Social clubs.
• On-site barista.