Data Science Developer (Retail) - Bryanston/Centurion
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Salary
≈ $20k – $50k per year (Estimated)
Location
In office (Centurion)
Seniority
Middle · 3+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
Job Mail is a South African online job board offering a large selection of vacancies across the country and some positions abroad. Job seekers can search and apply for jobs online, upload a CV and receive job alerts, while employers and recruitment agencies can advertise positions to a broad national audience. The brand is one of the longer-established names in South African job advertising and is operated from South Africa.
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.
- 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.
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