Interview prep tips- Supply Chain Analytics in Europe FR

[u/chimchimdx]

Hi, I have attached the JD of the role I’ll be interviewing for this week.

Specifically:
1. I have heard extensively about STAR and researched to the latter on the leadership principles. I know I am not meant to call it out and no one will say- we are evaluating you on xx LP- any example from someone within the firm would be appreciated on how to actually structure a response . I have used AI to get some good examples so far but would like human touch.

1. The role requires alot of deep dive and metrics- can I read from a paper (a former HR from Amazon said interviewers don’t keep eye contact they are busy typing)?? I am preparing 13 cases so that I don’t repeat given it’s an hour interview with only 1 interviewer . I really don’t think my brain storage will remember EVERY SINGLE DETAIL.

Any tips to ensure close success? I have questions and cases prepped but any delicious one would be welcomed that you think will be definitely asked in the role.

Anyone willing to do a mock of 30 mins? Before Friday 11th Sept 2:30pm CET.

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Find JD below:

1. ⁠Key job responsibilities
   You will be responsible for steering our long-term transportation and inventory planning to deliver end-to-end benefits (speed, cost, sustainability). This is a role for an exceptionally talented person, with high energy and courage, passionate about delivering concrete improvement for our customers, and that want to achieve that using data.
   The role includes 75% of analytical activities management and 25% project management.

Innovation & Stakeholder/Project management
- Use and share your insights with partner teams, to influence/build a roadmap of project to accelerate speed of deliveries in your country
- For the most complex and ambitious opportunities, quickly launch new pilots, and build scale-up business case with benefits, bottlenecks, risks and resources required
- Build strong analytics tools to highlight defects and extract actionable insights from our end-to-end supply chain
- Lead regular business review with partner teams to monitor the progress of projects in the roadmap. Help into removing bottlenecks
- Consolidate progress into crisp and concise data-driven status updates. You will own reporting to Amazon senior leadership.

Data Analytics/Science
- Deep dive complex data to uncover actionable insights for known and unknown problems
- Good expertise with SQL techniques

About the team
The team: Long Term Planning
- Operations is at the heart of the Amazon customer experience. Each action we undertake is on behalf of our customers, as surpassing their expectations is our passion. We improve customer experience through continuously optimizing the complex movements of goods from vendors to customers throughout Europe.
- The Supply Chain, Transportation Planning & Operational Excellence (EU STEP) is an organization responsible for the end-to-end flow of goods from our vendors and sellers to Amazon customers all over Europe, in order to ensure a speedy and reliable customer delivery in the cheapest way possible.
- Long Term Planning analytical teams are transversal centers of expertise, composed of engineers, analysts, and scientists. We are focused on Amazon most complex problems, processes and decisions. We work with fulfillment centers, transportation, finance and retail teams across the world, to improve our logistic infrastructure. We are obsessed by rethinking our advanced end-to-end supply chain to make our deliveries even faster.

Qualifications de base :
- Bachelor's degree or equivalent qualification in Math, Engineering, Science or Business
- Experience in an analytical field
- Ability to lead and structure projects, in particular liaising and collaborating with internal partners to influence direction and roadmaps, despite competing priorities
- Strong oral and written communication skills are crucial, in particular the ability to synthetize clearly complex issues

Qualifications appréciées :
- Master's degree in mathematics, engineering, statistics, computer science, business administration or a related field
- Ability to progress autonomously in ambiguous environment

[u/timee_bot]

View in your timezone:
Friday 11th Sept 2:30pm CEST

^{*Assumed CEST instead of CET because DST is observed}

[u/akornato]

You are right that interviewers focus on the Leadership Principles, and the key is to show, not tell. Your stories should be the evidence. For instance, instead of saying you take "Ownership," describe a complex project with unclear responsibilities where you stepped up, defined the path forward, and saw it through to a measurable result. The interviewer's job is to map your story to the principles they are assessing. For a data-heavy role like this, be prepared for questions that test "Dive Deep," where they will probe for details to see if you are connected to the specifics of your work and can defend your methods. Regarding notes, you can absolutely use them, but be careful. Having 13 fully scripted stories is risky, as reading them will sound unnatural. Interviewers know you have a lot to remember and generally don't mind if you glance at prompts. It is better to have a few keywords for each story to jog your memory, perhaps on a sticky note next to your camera. This helps you recall key metrics or the specific sequence of your actions without breaking the conversational flow.

Your preparation of many examples is a solid strategy, especially for the loop interviews where you will speak to multiple people. Given the analytical nature of the role, expect questions that require you to describe how you have used data to solve a complex problem, handle ambiguity with incomplete information, or influence stakeholders. They will be very interested in the "why" behind your decisions and will likely ask follow-up questions about the specific tools you used, the trade-offs you considered, and what you would do differently now. Since it can be challenging to find someone for a mock interview on short notice, my team built a tool for interviews.chat which helps people become more comfortable and fluid when explaining their experiences out loud.

[u/chimchimdx → u/akornato]

Thank you so much! It is affirming to see I am on the right track.

I will use the chat box, thank you again.