IT – Analyst, Data Management
Stellenbosch – Western Cape
HELP automate and improve processes through Data Science while designing and implementing Machine Learning Models as your technical expertise as a highly analytical Data Scientist is sought by an innovative Financial Services Provider to join its team. You must hold a suitable Honours Degree with 2-5 years’ work experience in Data Science, Machine Learning and the integration of developed solutions with Business Analysis and requirements gathering experience including proficiency in Spark, Hadoop, Big Data, Git, Bitbucket, Azure, AWS, SourceTree and Machine Learning development and underlying theory and assumptions of techniques.
- Assist in building and delivering the AI strategy to ensure the business is able to compete in a fast-changing landscape where Data Science is a key future-oriented strategic differentiator.
- Help automate and improve processes through Data Science, and create new products and services, and assist with improved decision making based on data.
- Design and implement Machine Learning models to better understand the drivers of business performance and enable improved management decision-making.
- Honours Degree.
- Master’s Degree (Ideal or Preferred).
- 2-5 Years working experience in Data Science, Machine Learning and integration of developed solutions.
- Business analysis and requirements gathering.
- Reproducible coding experience and working with source control tools e.g., Git, Bitbucket.
- Experience in deploying models into production.
- Spark, Hadoop or similar Big Data coding experience.
- Working in remote environments, e.g., Docker, Linux.
- Working in cloud environments, e.g., Azure, AWS.
- Solution and experimental design for model development.
- Machine Learning development and underlying theory and assumptions of techniques.
- Predictive Modelling techniques (Statistical and Machine Learning) and deployment.
- Source Control systems e.g., Git, Bitbucket, or SourceTree.
- Relational database technologies.
- Data Science lifecycle and applicable skills within.
- Exposure to leading in multiple functional/technical areas.
Ideal to have –
- Data Analysis.
- Solution and experimental design.
- Machine Learning model architecture (technical design and implementation processes).
- Specialist in one or more specific Machine Learning competencies, e.g., NLP, Deep Learning etc.
- Understanding of –
- Underlying theory and application of Machine Learning models must be able to understand underlying principles and theory and be able to teach others.
- Best practices for Data Science.
- Ethical AI Design principles.
- Data Science lifecycle.
- Analytical skills.
- Attention to detail.
- Communications skills.
- Numerical reasoning.