Quantitative Analyst

JVR Software; Durban; Presencial; ZAR 600 000 - 900 000; Tempo integral

Resumo da oferta

JVR Software in La Lucia, KwaZulu-Natal, seeks an experienced Data Scientist/Quantitative Analyst to develop and manage predictive models, build dashboards, and provide analytical insight to business units.

You will work with SQL, Python, and SAS on credit risk analytics, IFRS9 modelling, and large datasets, collaborating with stakeholders and delivering data-driven value.

Qualificações

• Honours degree in Statistics/Mathematics required.
• Masters degree preferred.
• Experience in credit risk analytics desirable.

Responsabilidades

• Develop and deploy predictive models aligned with business needs.
• Manage monthly monitoring and updates of existing models.
• Provide data analytics support and dashboards for business units.
• Collaborate with stakeholders to define data requirements and insights.

Conhecimentos

SQL coding

Advanced Excel

Python

Predictive modelling

Machine learning

IFRS9 modelling

Large data handling

Formação académica

Honours degree in Statistics/Mathematics

Masters degree in Statistics/Mathematics

Ferramentas

Denodo

SAS

Descrição da oferta de emprego

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

• 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
• 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
• 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
• Data development and maintenance
  Assist and advise on creating and maintaining data in an optimal manner

Education

• Honours degree in Statistics/Mathematics
• Preferred - Masters 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.