Adecco Data Scientist Interview Guide: Process, Questions & Prep (2026)

Written by Sakshi Gupta

Reviewed by Jay Feng

Table of contents

Introduction

Interview Topics

The Adecco Interview Process

Challenge

Featured Interview Question at Adecco

Adecco Data Scientist Interview Questions

Discussion & Interview Experiences

Introduction

Most candidates report 5 interview rounds over about three weeks, starting with a recruiter call followed by two technical interviews and a final discussion with a manager. The process focuses on machine learning project experience, data analysis reasoning, and the ability to explain modeling choices clearly, with interviewers asking candidates to walk through prior projects and analytical decisions. A commonly reported step is a timed technical exercise where candidates choose one of two data science problems and solve it within about 90 minutes before discussing their approach.

Interview Topics

Click or hover over a slice to explore questions for that topic.

Data Structures & Algorithms

(176)

SQL

(157)

Machine Learning

(120)

Product Sense & Metrics

(72)

Probability

(62)

The Adecco Interview Process

Resume or Profile Review

Adecco recruiters review resumes to confirm machine learning experience, programming languages such as Python or R, and exposure to real data science projects. Candidates report that the first contact is typically a short recruiter discussion that verifies background, availability, and whether the profile matches a specific client project. One candidate described the step as an initial meeting where the recruiter reviewed their CV before moving forward with the process.

Based on candidate reports.

Hiring Manager Screen

The recruiter screening usually lasts about 20 to 30 minutes and focuses on prior analytics or machine learning work and communication ability. Interviewers ask candidates to explain past data science projects, tools used, and the business impact of their work. One candidate summarized the round as a discussion where the recruiter asked them to “tell me about the projects that you worked on before.”

Based on candidate reports.

Technical Screen: SQL and Data Reasoning

Candidates frequently receive a technical exercise that tests applied data science problem solving. Reports describe a timed task where applicants choose one of two problems and work through it in roughly 90 minutes before discussing the approach with the interviewer. The exercise evaluates modeling decisions, data reasoning, and how clearly the candidate can explain their solution.

Based on candidate reports.

Technical Screen: SQL and Data Reasoning

Applied Analytics Case: Experimentation or Causal Reasoning

This stage is typically conducted by data scientists or technical managers and centers on machine learning concepts and project experience. Interviewers ask candidates to walk through prior models, discuss data preprocessing or evaluation choices, and answer conceptual questions about algorithms. One candidate described the interview as a discussion focused on explaining previous projects and analytical decisions.

Based on candidate reports.

Applied Analytics Case: Experimentation or Causal Reasoning

Stakeholder Interview

The final round is a discussion with a manager or client stakeholder responsible for the data science project. The conversation focuses on communication skills, collaboration with business teams, and how the candidate translates model outputs into business insights. Candidates report that this stage is relatively conversational and focuses on confirming fit for the team and project environment.

Based on candidate reports.