Quantitative Analyst

Hire Resolve; Durban; On-site; ZAR 600,000 - 800,000; Full time

Job summary

A leading analytics firm located in KwaZulu-Natal is seeking an experienced Data Scientist/Quantitative Analyst to develop and manage predictive models. The role involves analytical support to business units and the maintenance of accurate data and reporting. Ideal candidates will have an Honours degree in Statistics/Mathematics, with 2-5 years in credit risk analytics. Skills in SQL, Python, and machine learning are advantageous. This position requires a proactive personality and the ability to work under pressure while maintaining good time management.

Qualifications

• 2-5 years experience in scoring system development and credit risk analytics (retail).
• Preferred: 5-8 years of experience in scoring system development and credit risk analytics (retail), including 2 years at senior level.

Responsibilities

• Develop new predictive models and engage with key stakeholders.
• Manage and update existing predictive models monthly.
• Provide ad-hoc analytics/data science projects as needed.
• Assist in optimizing data maintenance.

Skills

SQL coding

Advanced Excel

Python

Denodo

SAS

Predictive modelling

Machine learning

Exposure to IFRS9 modelling

Education

Honours degree in Statistics/Mathematics

Master’s Degree in Statistics/Mathematics

Job description

An industry-leading company located in La Lucia, KwaZulu-Natal is currently seeking the expertise of an experienced Data Scientist/Quantitative Analyst.

Key Purpose

To develop, manage and monitor advanced and relevant predictive models, to provide advanced analytical support to business units, to critically analyze and advise the business on data-driven value adds, and create and maintain accurate data, dashboards, and management reports.

Key Outcomes

1. Model Development
   • Development of new predictive models in line with business requirements.
   • Successful deployment of predictive models.
   • Engagement with key stakeholders around business requirements for models.
2. Model Management
   • Manage monthly monitoring and regular updates of existing predictive models.
   • Prepare analysis/commentary for model management meetings.
   • Reporting to 3rd party funders on model management.
   • Ensure the model management process is conducted according to the policies defined.
   • Interrogate existing models and identify possible red flags.
   • Research the latest model building methodologies.
3. Data Analytics to support business needs
   • Ad-hoc analytics/data science projects as required by business.
   • Monthly analysis of key credit risk areas (loss control/credit).
   • Assist in building the Data science capabilities of the analytics team.
   • Proactive business engagement to understand the analytical requirement.
   • Proactive feedback to the business on value-added data-driven analytics.
   • Automation.
4. Data development and maintenance
   • Assist and advise on creating and maintaining data in an optimal manner.

Requirements

Education

• Honours degree in Statistics/Mathematics
• Preferred - Master’s Degree in Statistics/Mathematics

Experience

• 2-5 years experience in scoring system development and credit risk analytics (retail)
• Preferred: 5-8 years of experience in scoring system development and credit risk analytics (retail) - 2 of which are at senior level

Preferred Industry - Financial / Credit risk analytics

Skills

Technical (at least some of the below skills will be necessary)

• SQL coding
• Advanced Excel
• Python (advantageous)
• Denodo (advantageous)
• SAS (advantageous)
• Predictive modelling or financial modelling
• Machine learning (advantageous)
• Exposure to IFRS9 modelling (highly advantageous)
• Ability to work with large amounts of data

Generic competencies

• Analytical, critical and logical thinker
• Understands the need for data-driven decisions
• Ability to read and assimilate a specification of data requirements
• Proactive personality
• Tolerance to change
• Attention to detail
• Accountability and ownership of work tasks
• Self-motivated
• Ability to work within a team and as an individual
• Comply with project management protocol
• Enthusiasm/interest in credit risk management
• Sense of humour
• Resilience
• Tenacity
• Ability to work under pressure
• Good time management.