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Orange Data Scientist Interview Questions
& Process

Real candidates share what happened, how many rounds they had,
and how the experience turned out.

Based on 37 interview experiences · FREE TO READ

2.1 Rounds average
Average Typical difficulty
73% Positive experience

Candidate interview experiences

First-hand accounts from people who interviewed at Orange.

Showing 3 of 37
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Orange

Data Scientist

Analytics · a year ago

Entry Average Positive experience Accept offer 3 rounds
Interview process
Recruiter call Technical screen Onsite Offer
Interview formats
Behavioral Technical Coding

So, for the Junior Data Scientist job at Orange Maroc, they really wanna see if you're good with numbers AND if you're a good fit. First, you apply online. Then, there's a chat with HR about why you want to work there and what you studied, and if you're into their digital stuff. After that, it's a tech test, maybe some coding, or looking at data, or talking about ML, stats, and how to use Python, SQL, or Spark. Then you'll meet with a manager or someone on the data team, and they'll want to know how you solve problems, what you did in past projects (like school or internships), and how you could actually help with their business problems. Finally, they'll give you feedback, and if it's a go, you get an offer. They're looking for people who know their stuff but are also curious, can roll with the punches, and work well with others.

Confirmed questions1 question
  • Could you detail a data science project you completed, from beginning to end, covering the business goal, your tech stack, any hurdles, and the outcomes?
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Orange

Data Scientist

Analytics · more than a year ago

Mid Average Positive experience Accept offer 1 round
Interview process
Technical screen
Interview formats
Technical Coding Behavioral

You'll likely need to show off your Python, R, or other programming chops. Get ready to code or talk through code. Brush up on stats and math stuff like distributions, hypothesis testing, and ML algorithms. You might get asked about modeling, how to check models, and cross-validation. For ML and data analysis, be prepped to chat about the algorithms you've used, how you picked features, and how you tweaked hyperparameters. It's common to be asked to tackle a real-world or made-up problem, often as a case study. Make sure you can walk through your plan, why you chose it, and what you found.

Confirmed questions1 question
  • Could you explain how LLMs are structured and how they differ from Deep Learning models?
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Orange

Data Scientist

Analytics

Mid Average Negative experience Decline offer 3 rounds
Interview process
Recruiter call Technical screen Onsite Offer
Interview formats
Behavioral Technical Presentation

After you apply online with your resume and cover letter, recruiters will review your profile to see if you fit the job and have the skills we need. If you match, we'll call you in about 15 days for a first chat. Then, you'll have an interview with a recruitment consultant (video or in person). This chat is to get to know you, make sure you understand the role, and discuss your motivations and goals. We'll also talk about your work history, skills, salary expectations, and career growth. Depending on the role, you might take a personality test or a technical test to assess your profile or abilities. If the consultant interview goes well, you'll meet with one or more managers from the team. These meetings will clarify your tasks, see if you'd fit with the team, and dive deeper into the technical and behavioral skills needed. If we decide to move forward, we'll send you a job offer by email. We'll also help you get settled in once you accept.

Confirmed questions1 question
  • Tell me about a project you completed.

Orange Data Scientist Interview Questions

Quoted word for word from Orange interview reports.

What is the difference between supervised and unsupervised learning?

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What is the difference between supervised and unsupervised methods?

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Can you explain the random forest algorithm to someone completely unfamiliar with it?

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Could you explain how LLMs are structured and how they differ from Deep Learning models?

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Can you explain the various kinds of machine learning?

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Was the optimization problem required to be solved using a specific method?

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Why do you believe Data Science is an important field?

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Formats, difficulty and experience

Across all 37 Orange interview reports.

Interview formats

Behavioral 41%
Technical 38.5%
Coding 10.3%
Presentation 6.4%
Other 2.6%

Interview difficulty

Easy 29.7%
Average 56.8%
Difficult 13.5%

Candidate experience

Positive 73%
Negative 13.5%
Neutral 13.5%