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Senior Data Scientist
Remuneration: | negotiable |
Location: | Cape Town, Woodstock |
Remote work: | Some remote work allowed |
Job level: | Mid/Senior |
Type: | Permanent |
Company: | Hello Talent |
Senior data scientist
Location: Woodstock, Cape Town
Salary: R85,000 per month
About the role:
As a senior data scientist, you will play a key role in assessing, analysing, and mitigating risks within the company. You will oversee and complete the full model development cycle, from data extraction to presenting findings to relevant stakeholders. This role requires a deep understanding of data and modelling standards, credit scoring principles, and machine learning techniques.
Requirements:
- A degree in mathematics, statistics, data science, or a related quantitative field.
- At least five years of experience in credit data science within retail, insurance, or financial services.
- Strong understanding of credit risk models and advancements in machine learning techniques applicable to credit scoring.
- Comprehensive knowledge of IFRS9 principles, including their application in credit risk management, Expected Credit Loss (ECL) calculations, and impairment assessment methodologies.
- Excellent analytical skills to interpret complex financial and trade data for informed decision-making.
- Outstanding communication and presentation skills, with the ability to explain complex concepts to non-technical stakeholders.
- Proven leadership experience, including mentoring junior team members.
- Ability to excel in a fast-paced and dynamic environment while managing multiple priorities effectively.
- Familiarity with SME lending practices and challenges, including industry-specific risk factors, is highly desirable.
- Proficiency in tools such as Databricks, SQL, R, or Python.
- Monitor the performance of SME portfolios, identifying trends and potential risks, and recommending risk mitigation strategies.
- Manage the strategic direction of the portfolio, balancing risk and sales objectives.
- Oversee the development and maintenance of risk models and methodologies to manage credit risk exposure.
- Build scorecards and other credit risk models throughout the credit lifecycle.
- Collaborate with cross-functional teams, including finance, operations, and compliance, to align 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 regulatory changes, particularly IFRS9 requirements, ensuring compliance in credit risk management and reporting.
- Provide guidance and mentorship to team members, fostering a culture of continuous learning and professional development.
Posted on 18 Nov 16:00, Closing date 17 Jan
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