Data Analyst - Prescriptive Analytics R750 000 - R960 000

Introduction
Create measurable business value for internal and external clients by working with them to ask great business questions, employing leading, fit-for-purpose analytical methods and techniques, to provide data-driven insights to answer these questions, with a big focus on Prescriptive Analytics and Predictive Modelling.

Duties & Responsibilities

1. Engage with internal business clients with business questions, always probing for the deeper questions and needs, to find the best possible solutions for the business.
2. Play a key communication role between business and technical teams to ensure business context is retained when building analytical and data-driven solutions.
3. Build a deep contextual understanding of the business and the data to design and propose new solutions that could add meaningful business value.
4. Work closely with the data provisioning team to ensure they can provide the reliable, consistent, and context-rich data assets that the team requires for data use cases.
5. Create algorithms and build machine learning models to enhance product offerings and solve business problems.
6. Create monitoring and anomaly detection systems to track model performance.
7. Presentation of data science opportunities and model outcomes to a variety of stakeholders with a varied understanding of data principles.

Desired Experience & Qualification

1. Undergraduate degree / diploma in Mathematics, Statistics, Engineering, Physics, Finance, or Economics (or similar).
2. Knowledge and execution capabilities of common data structures, languages, and tools (e.g. SQL (must), Python or R (must)).
3. Experience or familiarity with data science model operationalization on-prem or in the cloud (GCP or Azure preferred).
4. Understanding and interpretation of statistics and data with a foundational knowledge of regression analysis.
5. An understanding (must) of Machine Learning techniques (supervised and unsupervised learning).
6. Practical experience preferred.
7. Experience working in a high-paced environment, where prioritisation is essential.

Package & Remuneration
R - R pa