This is a typical three-stage interview framework for a Simulation Research Engineer (in the Routing team) role. It's designed to assess open-ended problem solving, analytical depth, statistical reasoning and behavioural alignment through practical evaluation, manual CV screening and calibrated scoring. Built for fairness, clarity and compliance, share with you to support.
This past week, I’ve been building out a structured interview process for a Simulation Research Engineer (Routing) role, in Fulfilment Simulations teams.
Working closely with the hiring team, we designed a three-stage process that assesses open-ended problem solving, analytical depth, statistical reasoning, and communication skills, while maintaining fairness, transparency, and consistency throughout.
The focus is not just on technical knowledge, but on demonstrable reasoning ability in ambiguous, real-world scenarios.
We agreed on a structured three-stage process, supported by manual screening and a final calibration discussion. The candidate would have to spend 45 mins on analysing/presenting back a data report, prior to interview.
Recruiter-led
All CVs are reviewed manually by the recruiter.
No AI tools are used in filtering or screening applications.
At this stage, we are looking primarily for evidence of:
- Ability to reason about open-ended problems
- Masters / Phd level education (ideally STEM)
- Experience conducting deep, exploratory analysis
- Analytical work in industry, research, or academic settings
We are not screening purely for specific tools or technologies, but rather for demonstrated problem-solving depth - but highlyweighted to higher education backgrounds
This initial conversation is designed to assess:
- Suitability and motivation for the role
- Previous analytical experience
- Evidence of in-depth problem solving
- Ability to clearly explain technical work
- High-level structured reasoning
Candidates are also asked to walk through a past analytical project in detail, explaining:
- The problem
- The data involved
- Their methodology
- Key challenges
- What they learned
This stage evaluates communication, analytical depth, and overall alignment.
Format:
- Introduction
- CV discussion (brief)
- Case study exercise
- Candidate questions
Candidates are presented with an open-ended scenario and asked to explain:
- What data they would request
- How they would approach the problem
- How they would structure their thinking
- How they would handle uncertainty
Preparation is intentionally minimal to assess real-time reasoning.
Scrorecard: We assess:
- Communication
- Understanding of the problem
- Clarity of thought
- Generating ideas
- Handling ambiguity
- Inquisitiveness
- Ability to receive and incorporate feedback
Candidates are sent an exercise in advance and asked to:
- Submit a written report prior to interview
- Deliver a 10-minute presentation
- Participate in a technical discussion (30–40 minutes)
Scorecard: During the discussion, we assess:
- Justification of chosen methodology
- Statistical understanding
- Analytical depth
- Ability to defend decisions logically
- Openness to feedback
- Structured communication
This stage evaluates both technical capability and clarity of explanation in a panel setting.
The submitted report is assessed independently using a structured scorecard.
This allows us to evaluate:
- Quality of writing (clarity, structure, readability)
- Depth and rigour of analysis
- Logical flow
- Strength of conclusions
Separating written and verbal assessments ensures a fair and balanced evaluation.
A structured competency-based interview assessing:
- Collaboration
- Ownership
- Communication style
- Problem-solving approach
- Alignment with team values
This stage ensures both technical capability and team fit are
All candidate materials, including CVs, assessments, written reports, and presentations, are treated as confidential and used solely for the purpose of evaluating suitability for the role.
Access is restricted to relevant interviewers and hiring stakeholders. Materials are stored and processed in accordance with applicable data protection regulations and internal data governance policies. No candidate answers are shared in this document.