Coles Group Data Scientist interview questions & guide 2026

While the interview process can vary by team, the following questions reflect the core competencies required for the Data Scientist role at Coles Group. Use these as a framework to understand the patterns of inquiry rather than as a static list to memorize.

Product Sense and Metrics

This category evaluates your ability to translate business requirements into measurable outcomes and assess the health of a product or service.

• How would you design a metric to measure the success of a new loyalty program feature?
• A key performance metric has suddenly dropped by 10%; walk me through your diagnostic approach.

Preparation for Coles Group should be grounded in both technical fluency and business context. You should aim to demonstrate that you can bridge the gap between complex algorithms and the practical realities of a large-scale retail business.

Role-related knowledge – You must be comfortable with the end-to-end data science lifecycle, from data extraction to model deployment. Expect to be tested on your ability to write efficient SQL and your deep understanding of statistical testing frameworks.

Problem-solving ability – Interviewers will look for a structured approach to ambiguous problems. When presented with a case study, always clarify assumptions, define your metrics, and outline your methodology before diving into technical details.

Leadership and influence – Even in technical roles, Coles Group values candidates who can advocate for their work. Demonstrate your ability to influence product roadmaps by showing how your data insights align with broader company objectives.

Culture fit – Coles Group is a collaborative environment. Show that you are a team player who values cross-functional input and can remain resilient and professional when projects do not go as planned.

The interview process at Coles Group is designed to assess your technical depth, your ability to think strategically about product metrics, and your alignment with the company’s collaborative culture. You can generally expect an initial screening call followed by a series of technical and behavioral interviews. The pace is professional, and you should be prepared for deep dives into your past projects and hypothetical problem-solving scenarios.

The visual timeline above illustrates the standard progression from initial contact to the final decision. Candidates should treat each stage as a distinct opportunity to showcase a different facet of their expertise, ensuring they have prepared examples for both technical execution and stakeholder management. Remember that the process may be tailored based on the specific team or seniority level of the role.

Experimentation and A/B Testing

This is a critical area for Coles Group. You must be able to design experiments that are robust and interpretable.

• Statistical significance – Understanding p-values, confidence intervals, and power analysis.
• Experimentation pitfalls – Identifying biases, such as selection bias or interference between variants.
• A/B testing methodology – Designing randomized controlled trials in a real-world, noisy retail environment.

As a Data Scientist, your primary responsibility is to turn data into actionable intelligence. You will be expected to:

• Lead the design and execution of A/B tests to optimize customer-facing features and marketing campaigns.
• Write complex SQL queries to extract and clean data from large-scale data warehouses.
• Build and maintain predictive models that support inventory management and supply chain logistics.
• Partner with product managers to define success metrics for new features and monitor these metrics for anomalous drops or spikes.
• Communicate technical findings clearly to stakeholders to drive business strategy.

A strong candidate for this role possesses a blend of high-level technical skills and a pragmatic business mindset.

• Technical skills – Proficiency in SQL (including window functions), Python or R, and experience with statistical modeling and experimentation tools.

• Experience level – A solid background in applying data science in a commercial or product-focused setting is essential.

• Soft skills – Strong communication skills are non-negotiable; you must be able to translate technical jargon into business value.

• Must-have skills – SQL (window functions, joins, complex aggregations), A/B testing design, statistical hypothesis testing, and product metric development.

• Nice-to-have skills – Experience with cloud data platforms, machine learning model deployment, and retail-specific domain knowledge.

Q: How much technical preparation should I prioritize? A: Prioritize high-impact technical skills like SQL and A/B testing, as these are frequently assessed. Ensure you can explain the "why" behind your technical choices, not just the "how."

Q: What is the best way to approach the behavioral interviews? A: Use the STAR method (Situation, Task, Action, Result) to keep your answers structured and focused. Ensure your results are quantifiable where possible to demonstrate impact.

Q: Is the culture at Coles Group collaborative? A: Yes, success at Coles Group often depends on your ability to work across teams. Highlighting your experience in cross-functional partnerships will resonate well with interviewers.

• Prepare for ambiguity: Many interview questions will be open-ended. Ask clarifying questions to narrow the scope before you start solving.
• Focus on the business: Always connect your technical solution back to how it helps the customer or the business.
• Know your resume: Be prepared to discuss any project on your resume in extreme detail, including the data challenges you faced.
• Practice SQL: Do not rely on basic queries; ensure you are proficient with window functions and complex joins.

The Data Scientist role at Coles Group offers a unique opportunity to apply sophisticated analytical techniques to a massive, real-world retail ecosystem. By mastering the fundamentals of SQL, experimentation, and product metrics, and by clearly articulating your impact through behavioral examples, you can significantly improve your standing. You can explore additional interview insights, practice questions, and preparation resources on Dataford.

The salary data provided reflects the compensation range for this role. Candidates should interpret these figures as a baseline, keeping in mind that final offers are often adjusted based on years of experience, specific technical expertise, and internal leveling processes.