# How to Ace Your Behavioural Interviews: Frameworks and Strategies for Data Scientists
## Preparation Is Everything
I used to think behavioural interviews were a walk in the park. Being confident in my own gifts, I thought that I would be the type they’d want to recruit, but I was wrong. The reality is that you cannot wing these sorts of interviews. Believe me, I tried and failed miserably.
Most candidates overlook behavioural interviews and fixate on the technical aspects of their applications. It is easy to think that because data science and machine learning are technical fields, interviewers and companies only care about your technical abilities.
**This couldn’t be further from the truth.**
I have seen people get hired solely because they were a good “culture fit” and the hiring team really liked how they approached their work. My friend **Mandy Liu** even got a $30k pay bump and was up-levelled from senior to lead data scientist before she was even hired due to her performance in the behavioural interview.
So, in this article, I want to break down the exact strategies and frameworks for you to do the same.
Let’s get into it!
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## What Are Behavioural Interviews?
Behavioural questions are designed to assess whether your values align with those of the company and whether the company can provide an environment for you to thrive and deliver your best work.
This interview is by far the most subjective of the whole process and is often conducted last by the hiring manager. **This shows you the importance of behavioural interviews.**
The hiring manager wants to ensure you are someone they and the rest of the team can work with. It’s also the levelling interview. Perform badly, and they may down-level you from senior to mid-level. Perform well, and they may up-level you from senior to lead, like what happened to Mandy.
Let’s now go over the key tips you need to ensure you get hired and increase your chances of getting up-levelled.
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## Story Vault
The first step is actually thinking about the stories you are going to use in the interview. Behavioural interviews are all about how you work and why you do certain things. This will require you to call up examples from past experiences to bring it to life.
So, I want you to sit down and review your resume to identify the 2–3 most impactful, longest, and most interesting projects you have completed.
> *They don’t always have to be data science or work-based, but it’s often best to keep them related to the field, as they translate better to what the interviewer is probing for.*
These are going to be part of your “story vault” that you are going to use for every single behavioural interview that you will do. This doesn’t mean you can’t respond to questions from other projects or work you have done, but these 2–3 will form the backbone of your responses, and you should know them inside out.
This will prevent any awkward moments in the interview where you have nothing relevant to draw upon; it’s always about preparation. The goal is to pick stories with enough depth and technical detail to support multiple questions.
You don’t need a different story for every behavioural question — 2 is completely sufficient (3 even better), and you will tweak your response to align with the question. If possible, have a story for:
– *One about a success*
– *One about a failure*
– *One about teamwork or leadership*
This will help you cover multiple bases.
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## Culture & Values Research
It’s unbelievable how many candidates don’t research the company before interviewing. I have interviewed over 50 people for data science and machine learning roles, and it’s clear that many haven’t researched the company’s values or cultural principles.
So, the obvious first step is to find the company’s values. This is really simple to do; all you need to do is Google:
> *”[Company] culture and value principles”*
Many companies have an overarching culture/value principle and multiple sub-principles. For example, DoorDash’s values and culture principles are:
– **We are leaders**
– **We are doers**
– **We are learners**
– **We are one team**
These are then further broken down into their own sub-principles. To be honest, most companies have the same principles, just worded slightly differently. For example, this is what DoorDash’s ones really mean:
– **We are leaders** → You take initiative and ownership over your work
– **We are doers** → You take action and don’t wait to be told what to do
– **We are learners** → You constantly look to up-skill and improve your abilities
– **We are one team** → You work collaboratively with others
This part is more involved, particularly if the company has many cultural/value principles. Go over every value and map out something from your “story vault” that demonstrates that particular value or culture principle.
At a minimum, you should include examples of the overarching culture/value principle; ideally, you should also cover the sub-principles. One example per principle is fine, but two is much better if you have the time and want to over-prepare.
This shouldn’t take you more than one hour, and they don’t need to be fully written out word-for-word; bullet points with rough context are sufficient. It’s more for you to have an idea of what you are going to say.
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## R-STAR-L Framework
Companies, interview coaches, and websites will all tell you to use the STAR method when answering interview questions, particularly behavioural ones. The STAR method stands for **Situation, Task, Action, and Result**. However, I believe this framework is incomplete. That’s why I recommend using the **R-STAR-L** framework, which adds two critical components: **Reflection** at the beginning and **Learning** at the end.
Here’s how it works:
– **R – Reflection:** Start by briefly reflecting on the context of the situation. Why was this project or challenge significant? What was at stake?
– **S – Situation:** Set the scene. What was the background and context of the story?
– **T – Task:** What was your specific role and responsibility in this situation?
– **A – Action:** What steps did you take? This is the most important part — be specific about what *you* did, not what the team did.
– **R – Result:** What was the outcome? Quantify your results whenever possible.
– **L – Learning:** What did you learn from this experience? How did it shape your approach going forward?
The addition of Reflection and Learning at the beginning and end elevates your answers from simply recounting what happened to demonstrating self-awareness and growth — exactly what hiring managers are looking for in behavioural interviews.
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## Final Thoughts
Behavioural interviews are not something you can afford to neglect. They can make or break your application, determine your level, and even impact your compensation. By building a strong story vault, researching the company’s culture and values, and using the R-STAR-L framework to structure your answers, you’ll be well-positioned to impress any hiring manager and land the role — and level — you deserve.
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*This article was adapted from the original post: [How to Ace Your Behavioural Interviews: Frameworks and Strategies for Data Scientists](https://medium.com/@nicholaslehoux/how-to-ace-your-behavioural-interviews-frameworks-and-strategies-for-data-scientists-8f5b3e7c2a1d)*# The Problem With Using the STAR Framework in Behavioral Interviews (And How to Fix It)
When it comes to answering behavioral interview questions, most candidates reach for the same tool: the **STAR framework**. And while it’s a popular approach for good reason, there’s a major problem with relying on it—**everyone is doing it, so you don’t differentiate yourself at all.**
## What Is the STAR Framework?
For those unfamiliar, the STAR method breaks down as follows:
1. **Situation:** Describe the scenario you were in
2. **Task:** Explain what you had to do
3. **Action:** Detail what you specifically did
4. **Result:** Share what happened as a result
There is nothing inherently wrong with STAR. It provides a useful structure for keeping your answers organized and concise. However, **it’s not optimal.**
## Why STAR Falls Short
Here’s the core issue: **STAR doesn’t directly tell the interviewer that you are a culture fit.** All you are doing is walking through previous work experience, which is not at all specific to the company you’re applying to.
Think about it—if an interviewer at one company asked you, *”Describe the most difficult challenge you overcame in the workplace,”* and another interviewer at a different company asked you the same question, your STAR response would be exactly the same. **That’s not good.**
A generic answer tells the interviewer *what* you’ve done in the past, but it says nothing about *why you’re the right fit for their team specifically.*
## Introducing the R-STAR-L Framework
This is where the **R-STAR-L** framework comes in. I’ve used this approach in all of my behavioral interviews, modifying the regular STAR method to include two additional elements. R-STAR-L stands for:
1. **Repeat:** Play back the question to ensure you’ve understood it and show you’re engaged
2. **Situation:** What was the scenario
3. **Task:** What you had to do
4. **Action:** What you did
5. **Result:** What happened as a result
6. **Link Back:** Explain why this result and scenario align with the culture and value principles of the company you’re interviewing with
Let’s break these two new elements down further.
### Repeat
The reason you want to repeat the question back to the interviewer is threefold:
– It shows them you are engaged in the interview
– It confirms you know the exact question you’re answering
– It gives you some extra time to think about your response
This may sound simple, but many candidates start answering a different question than the one that was asked. It’s sloppy and a big red flag for interviewers.
**Important note:** Don’t repeat the question back verbatim—rephrase it slightly. For instance, if asked, *”Tell me about a time you had a conflict with a coworker,”* you might say: *”Just to make sure I understand, you’d like me to walk you through a moment where I navigated a disagreement or tension with a colleague, correct?”*
### Link Back
This is where the magic happens.
After each answer, link it back to the company’s culture and value principles. However, don’t make it too obvious—slide this “linking” in naturally, or it will seem scripted and desperate. Most people will be able to read between the lines to understand what you’re doing.
The reason you link back is simple: you want to show them that you are indeed a **culture fit** for their company. Who wouldn’t want to hire someone who operates in a manner the company values?
By linking or mapping your response to their specific culture and value principles, you’re tailoring your answer and making it no longer generic. You’re telling them directly what’s in it for them if they hire you.
## Putting It All Together: An Example
Imagine you’re interviewing at **DoorDash** for a data scientist position, and they ask you:
*”Tell me about a time you identified a problem that wasn’t necessarily your responsibility.”*
This is your opportunity to showcase the **”Be an owner”** principle.
**Repeat:**
*”Just to clarify, you’re looking for an instance where I took the initiative to solve a problem or improve a process that fell outside my immediate project scope or ‘ticket’ description, right?”*
**Situation:**
*”In my previous role, I was assigned to build a dashboard in Tableau to track the delivery success rates for a specific geographic region. While I was auditing the SQL queries powering the dashboard, I noticed a recurring discrepancy—about 4% of orders were being flagged as ‘Failed Delivery,’ but they had no associated refund or customer support ticket.”*
**Task:**
*”Technically, my task was just to visualize the data as it existed. However, I realized that if 4% of our data was mislabeled, the dashboard would mislead the operations team. I felt it was my responsibility to investigate the root cause of this ‘ghost’ failure rate before finalizing the project.”*
**Action:**
*”I dug into the raw JSON logs in Snowflake and discovered a logic error in the mobile app’s delivery confirmation event. If a driver lost cell signal at the exact moment of drop-off, the system defaulted the status to ‘Failed’ even if the customer received the food. I didn’t just report the bug; I wrote a temporary SQL patch to correctly categorize those specific orders based on GPS coordinates. Then, I presented my findings to the Engineering lead with a clear breakdown of how this was skewing our performance metrics.”*
**Result:**
*”The Engineering team implemented a fix in the next sprint. By correcting the logic, the ‘Failed Delivery’ rate dropped to its true level of 1.5%, which saved the Operations team from launching an unnecessary—and expensive—driver retraining program. It also ensured that our regional performance data was 100% accurate for the first time in two quarters.”*
**Link Back (The “Be an Owner” Angle):**
*”I tend to look at projects through a product lens rather than just a technical one. If the underlying data is flawed, the dashboard is just a distraction for the Ops team with noise. I’d rather take the extra time to fix a root-cause issue I’ve stumbled upon than ship something I know isn’t 100% reliable, because at the end of the day, I’m responsible and the owner for the decisions that the data drives.”*
Mic drop.
Notice how the word “owner” was slipped in naturally at the end to implicitly demonstrate how the candidate meets that specific value and culture principle. Sometimes it will be hard to do this directly, but you should aim for **all** your responses to be structured this way.
## The Key Takeaway
The STAR framework gives you structure, but the **R-STAR-L** framework gives you structure *and* relevance. By repeating the question to show engagement and linking back to the company’s specific values, you transform a generic answer into a compelling, tailored narrative that proves you’re not just qualified—you’re the right fit.
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*Original article: [The Problem With Using the STAR Framework in Behavioral Interviews (And How to Fix It)]()*
