Junior Data Scientist

homechoice; Cape Town; On-site; ZAR 250,000 - 350,000; Full time

Job summary

homechoice in Cape Town is seeking a junior data scientist to support the Data Science team in developing, monitoring and improving statistical and machine learning models used across Credit Risk, Collections, Fraud and Marketing. You'll work with real business data in a fast-paced retail environment.

You will prepare data, build reports with PowerBI, and assist in model validation and automation while following coding standards.

Qualifications

• Undergraduate degree or equivalent in data science, statistics, mathematics, CS, engineering or related numerate field.
• Foundational to intermediate SQL, SAS, Python and Excel skills for data extraction and analysis.
• Knowledge of statistics, probability and machine learning concepts.
• Exposure to data science, predictive modelling or automation through projects or internships.
• Ability to write clear, well-documented code for repeatable analysis.

Responsibilities

• Prepare, clean and validate datasets for analysis.
• Identify trends and opportunities to support business decisions.
• Create PowerBI reports and data outputs for stakeholders.
• Monitor model performance and data quality across domains.
• Assist in feature preparation and model validation under guidance.
• Follow coding standards and document work for reuse.

Skills

SQL

SAS

Python

Excel

Data analysis

Education

Undergraduate degree in Data Science / Statistics / Mathematics / CS / Engineering

Tools

PowerBI

Excel

Job description

homechoice is a leading South African homeware retailer. For over 40 years we’ve helped our customers create beautiful homes they love with an innovative range of quality products they can afford.

The purpose of this role is to support the Data Science team with the development, monitoring and improvement of statistical and machine learning models that help guide business decisions across Credit Risk, Collections, Fraud and Marketing.

This junior-level role is ideal for an analytical, curious and technically minded individual who wants to grow practical data science experience in a supportive team while working with real business data in a fast-paced retail environment.

What You Will Love Doing In This Role

Data Preparation and Analysis

• Extract, clean, validate and analyse customer, product, credit and campaign data using SQL, SAS, Python and related tools.
• Identify trends, patterns and opportunities that support reliable business decision-making.

Reporting and Insight Delivery

• Prepare clear PowerBI reports, summaries and data outputs for stakeholders.
• Translate analytical results into practical, business-friendly insights.

Model Monitoring and Maintenance

• Monitor predictive models across Credit Risk, Collections, Fraud and Marketing.
• Track performance, data quality and unusual results, escalating issues where required.

Predictive Modelling Support

• Support model development, testing, validation and documentation under guidance.
• Prepare features, training datasets and performance summaries to support repeatable model review.

Best Practice, Coding Standards and Automation

• Follow coding standards, write reusable code and maintain clear documentation.
• Automate regular processes to reduce manual effort while maintaining output quality.

Use of AI Tools and Emerging Technologies

• Use approved AI tools to improve productivity, support coding, summarise outputs and explore analytical approaches.
• Validate AI-generated outputs for accuracy, relevance, business context and data governance compliance.

Collaboration and Continuous Learning

• Collaborate with data and business teams to understand requirements and deliver useful outputs.
• Continuously build knowledge of business processes, data science, machine learning, statistics and software development.

What you’ll need to do this role

Minimum Requirements

• Undergraduate degree or relevant qualification in Data Science, Statistics, Mathematics, Computer Science, Engineering, Information Systems or a related numerate discipline.
• Foundational to intermediate SQL, SAS, Python and Excel skills, with the ability to extract, clean, analyse and interpret structured datasets.
• Understanding statistics, probability theory, data analysis and machine learning concepts.
• Exposure to data science, machine learning, statistical analysis, predictive modelling, reporting or automation through academic projects, internships, graduate programmes, personal projects or early career work experience.
• Ability to write clear, structured and well-documented code that supports repeatable analysis, handover and future review.

Advantageous exposure

• Ongoing personal development in data science, statistics, AI or machine learning, such as online learning, certifications, portfolio work or personal projects.
• Exposure to retail, credit, collections, fraud, marketing, customer analytics or model monitoring

What We Will Love About You

• You are curious, analytical and enjoy solving problems using data.
• You have strong attention to detail and take pride in producing accurate work.
• You are comfortable learning new tools, asking questions and building your technical capability.
• You can translate data findings into simple, practical insights for business teams.
• You are collaborative, accountable and eager to contribute to a high-performing Data Science team.

Behaviors we love

Wow my customer

• Walk in my customers’ shoes
• Deliver on my promises
• Deliver insight-led solutions my customers needs

Treat the business as my own

• Take accountability
• Be curious, creative & explore opportunities
• Do it right & at the right time

Play as a team

• Be helpful
• Be inclusive
• Find the fun