Happy Monday, Reader! When you take your first job interview in English, you might notice a lot of “Tell me about a time you…” instead of direct questions about your hard skills.

Today you will learn how to:

• understand cultural nuances in English interviews

• prepare for behavioural questions using story banks

• structure your answers with STAR-F to get a more senior role

INTERVIEWS

Behavioural Questions

What are behavioural questions? Candidates are asked to give specific examples of when they demonstrated particular behaviors or skills to see how well they align with the role. 

For example “Can you tell me about a time you had to resolve a conflict between team members?”

More example questions

3 important tips:

• Western interviews place a huge focus on soft skills. When comparing interview styles with the East, western companies usually use more behavioural rounds than coding or technical rounds.

• The quality of your answers can determine what level you qualify for. Answers focused on impact at the project level = junior, impact within the team = mid-level, impact on company strategy/goals = team lead/senior

• You only need to use what you already know! Focus on showcasing your existing skills and experience rather than trying to cover unfamiliar areas. In terms of ROI (return on investment), you’ll benefit the most from focusing on behavioural interview preparation.

How to prepare for behavioural questions?

1. Create a good story bank

2. Work on the answer structure (STAR, STAR-F)

3. Practice, practice, practice!

INTERVIEWS

STAR-F Structure

You’ve probably heard about the STAR structure, but what about STAR-F?

F stands for Framework and this part of your answer should describe the system or toolset that you’ve developed/used to repeatedly solve this situation.

This is especially important for senior/leadership roles - you can uplevel yourself by showing that you have a framework that you can consistently apply based on your years of experience.

Example Question: Tell me about a complex technical problem you’ve worked on. How did you go about solving it?

Example bullet point notes from a story bank:

• Situation: Team receives financial market data from various sources in different formats, structures, levels of granularity 

• Task: Create automated process to standardise and consolidate data into one database

• Action: Used expertise of team mates to better understand data, created a data dictionary to standardise column headers, python scripts to clean and transform data, implemented validation checks on all processes

• Result: Streamlined pipeline of 30+ years of data, validated to 0.0001% accuracy, decreased lead time by 50%

• Framework: Created a workflow for other team mates to follow & wrote documentation to explain how to use the data dictionary and validation script in their pipelines

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