Data Science Developer (Retail) - Bryanston/Centurion

Headhunters; Randburg; On-site; ZAR 700,000 - 1,200,000; Full time

Job summary

Headhunters client in the retail sector seeks a Mid-Level Data Scientist / Data Science Architect / Data Science Developer for Bryanston or Centurion. You will work on innovative data products and analytics solutions that drive business value.

Responsibilities include designing data architectures, building robust data pipelines, developing ML models and deploying them into production, while collaborating with diverse stakeholders to translate business needs into technical outcomes.

Qualifications

• Bachelor's or master’s degree in a quantitative field.
• Postgraduate qualification is advantageous.
• Minimum 3 years in data science, analytics or ML engineering.

Responsibilities

• Design data architectures for advanced analytics and ML delivery.
• Build, optimise and maintain data pipelines from multiple sources.
• Develop, deploy and maintain ML models and analytical solutions.
• Collaborate with stakeholders to deliver practical data solutions.
• Evaluate new data sources and technologies for commercial opportunities.
• Prototype new data-driven products and features.

Skills

SQL

Python

Power BI

Data architecture

Machine learning

ETL/ELT

Data pipelines

Analytical skills

Communication

Agile

Education

MSc / MSc in Data Science / Statistics / Mathematics / CS

BSc Honours

Job description

Our client in the retail industry is seeking to employ a Mid-Level Data Scientist / Data Science Architect / Data Science Developer to join their team based in Bryanston or Centurion.
Exciting Opportunity:
Join a dynamic and forward-thinking team where your data science, machine learning and data engineering skills will make an immediate impact. This role offers the opportunity to work on innovative data products, advanced analytics solutions and commercially valuable projects while collaborating with both internal and external stakeholders.

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.