Job title: Senior Data Analyst
Job type: Permanent
Emp type: Full-time
Salary: ZAR 700,000.00
Job published: 26/11/2019
Job ID: 38411

Job Description

Senior SAS DATA ANALYST / CREDIT RISK ANALYST – develop Strategic STATISTICAL MODELS & GAIN DATA SCIENCE SKILLS with leading data-driven RETAILER – CAPE TOWN:

This is an excellent opportunity for a Senior DATA ANALYST / CREDIT RISK ANALYST to join a leading data-driven RETAILER, and within a team develop STATISTICAL MODELS for Strategy Development, and GAIN DATA SCIENCE (MACHINE LEARNING) skills and experience.

Based in CAPE TOWN this is a SENIOR role offering a salary reflecting this level.

THE COMPANY:
This established Retailer is a data-driven business with an impressive market-share and track record of success. With highly advanced CRM, Data Management, BI, Analytics and Data Systems their success hinges around their ability to make accurate, quick business decisions based on rules supported by their data assets.

The ANALYTICS and CREDIT RISK TEAMS are rapidly moving into DATA SCIENCE initiatives, where Machine Learning and Automation offer the prospects of enhancing their Decisioning Systems, Decision Rules and accuracy. These are exciting times and you will have the opportunity to grow with the team on this exciting journey. The team is responsible for the full customer strategy and as such this is a key position.

THE ROLE:
Your role will be varied and will include ad hoc analyses; the development of statistical models for strategy development (using SAS technologies); monitoring and tracking of existing models and reporting; and gaining Machine Learning, Python, and Data Science experience.

REQUIRED SKILLS:
BCom / BBusSci / BSc Actuarial Science / BCom Investments or similar qualification - majoring in Statistics with a strong academic record.
Experience in building, implementing and using statistical models for strategy development.
SAS Base / SAS Enterprise Guide programming experience.
Experience in a retail or financial services industry with specific collections or recoveries experience.
Experience with bureau data will be beneficial.
Some experience with Python and Machine Learning.
Excellent analytical and numeric skills.