Data Science Developer (Retail) - Bryanston/Centurion

Headhunters; Centurion; On-site; ZAR 670,000 - 1,004,000; Full time

Job summary

Headhunters is seeking a Data Science Developer (Retail) to design scalable data architectures and deliver ML-driven analytics. You will build robust data pipelines, deploy ML models, and collaborate with multiple stakeholders to translate business challenges into practical data solutions.

The role requires 3+ years in data science or analytics engineering, with advanced SQL, Python and Power BI skills, and an ability to prototype production-ready analytics within a retail context.

Qualifications

• BSc Honours or MSc in a related field preferred.
• Postgraduate qualification advantageous.
• Very strong SQL, Python and Power BI skills.
• Experience designing data architectures and pipelines.
• Proven ML/analytics production experience.

Responsibilities

• Design and improve data architectures for analytics and ML delivery.
• Build, optimise and maintain data pipelines from multiple sources.
• Develop, deploy and maintain ML models and analytical solutions.
• Collaborate with business and production stakeholders to deliver data solutions.
• Investigate new data sources and technologies for commercial opportunities.
• Prototype new data-driven solutions and translate business challenges into technical ones.
• Support and improve existing predictive models and decision-support tools.
• Contribute to code quality, documentation and deployment processes.
• Provide input into technical direction and architecture decisions.
• Share knowledge through coaching, presentations and updates.
• Estimate work, prioritise tasks and deliver on deadlines.

Skills

SQL

Python

Power BI

Data architecture

ML engineering

ETL/ELT

Agile

Stakeholder management

Team collaboration

Communication

Education

BSc Honours / MSc

Tools

Power BI

Job description

Data Science Developer (Retail) - Bryanston/Centurion

Reference PE003840

Location Gauteng, Centurion

Salary Interval Monthly

Package None-negotiable

Description Requirements:

• BSc Honours / MSc in Statistics, Mathematics, Computer Science, Data Science, Engineering or a related field preferred.
• Relevant postgraduate qualification advantageous.
• Minimum 3 years of relevant experience in data science, analytics engineering, machine learning engineering or a related field.
• Proven experience designing data solutions, building data pipelines and delivering machine learning or advanced analytics projects in production environments.
• Very high proficiency in SQL, Python and Power BI.
• Strong experience in data architecture and data pipeline design.
• Strong machine learning engineering experience, including model development, deployment and maintenance.
• Experience with data modelling, ETL/ELT processes and performance optimisation.
• Strong analytical, statistical and problem-solving capabilities.
• Experience designing scalable data workflows and integrating multiple data sources.
• Ability to prototype and productionise analytical and machine learning solutions.
• Familiarity with software engineering best practices, version control and testing principles.
• Proficient in Microsoft Office, with advanced Excel advantageous.
• Professional report writing, documentation and technical communication skills.
• Familiarity with Agile concepts and their application in data science and product development.
• Experience working with logistical and/or geographic data will be advantageous.
• Strong attention to detail and a passion for data, analytics and innovation, particularly within retail and/or insurance.
• Strong communication and stakeholder management skills.
• Ability to work effectively both independently and as part of a team.
• Client-centric approach with the ability to engage confidently with technical and non-technical stakeholders.
• Growth mindset with a passion for continuous learning and innovation.

Responsibilities:

• Design and improve data architectures that support advanced analytics, machine learning solutions and scalable product delivery.
• Build, optimise and maintain robust data pipelines for the ingestion, transformation and delivery of data from multiple internal and external sources.
• Develop, deploy and maintain machine learning models and analytical solutions.
• Collaborate with business and production stakeholders to deliver practical, high-impact data solutions.
• Investigate and evaluate new data sources, technologies and approaches to identify commercial opportunities.
• Drive innovation through prototyping and the development of new data-driven solutions, products and features.
• Translate business challenges into effective technical and analytical solutions.
• Support and improve existing predictive models, analytical products and decision-support tools.
• Contribute to best practices in code quality, documentation, solution design and deployment processes.
• Provide input into technical direction and architecture decisions.
• Identify opportunities for continuous improvement across data science and product development initiatives.
• Analyse, interpret and communicate complex data to support business decision-making.
• Work with stakeholders across different teams and client environments to understand requirements and deliver fit-for-purpose solutions.
• Share knowledge through peer coaching, technical discussions, team presentations and broader business updates.
• Estimate work accurately, prioritise effectively and deliver projects within agreed deadlines.
• Contribute to the development of scalable, commercially valuable data products and proof-of-concepts.