Deloitte Machine Learning Engineer Interview Questions + Guide in 2024
Overview
Deloitte is a global professional services firm renowned for innovative strategies and impactful solutions across industries. It stands at the forefront of leveraging data, robotics, and AI to drive transformative results for its clients.
As a Machine Learning Engineer at Deloitte, you’ll develop and deploy machine learning models, utilize cloud platforms, and collaborate closely with cross-functional teams to optimize solutions. This role is pivotal in uncovering hidden data relationships and enhancing decision-making processes for public sector clients.
If you’re ready to bring your expertise to a leading firm and tackle impactful projects, this guide will help you navigate the interview process and crack the typical Deloitte machine learning engineer interview questions. Let’s dive in!
What Is the Interview Process Like for a Machine Learning Engineer Role at Deloitte?
Recruiter/Hiring Manager Call Screening
If your CV is among the shortlisted few, a recruiter from the Deloitte Talent Acquisition Team will contact you and verify key details like your experiences and skill level. Behavioral questions may also be part of the screening process.
Sometimes, the Deloitte Machine Learning Engineer hiring manager stays present during the screening round to answer your queries about the role and the company itself. They may also indulge in surface-level technical and behavioral discussions.
The whole recruiter call should take about 30 minutes.
Online Assessment
The first stage involved psychological tests, followed by abstract reasoning and critical thinking games with a time limit. At this stage, there is no in-person interview. Instead, pre-arranged questions are provided, and the company records your video responses. For example: - “In what situation do you have to work in a group setting?”
Technical Virtual Interview
Successfully navigating the recruiter round will invite you to the technical screening round. Technical screening for the Deloitte Machine Learning Engineer role is usually conducted virtually, including video conferences and screen sharing. Questions in this 1-hour interview stage may revolve around Python programming, machine learning algorithms](https://www.interviewquery.com/p/machine-learning-algorithm-interview-questions), and libraries related to data science, like pandas and NumPy. Topics may include:
- Overfitting and underfitting
- Variance and bias tradeoff
- Describing any specific algorithm in detail
Case studies and similar real-scenario problems may also be assigned depending on the position’s seniority.
Onsite Interview Rounds
Followed by a second recruiter call outlining the next stage, you’ll be invited to attend the onsite interview loop. Multiple interview rounds, varying with the role, will be conducted during your day at the Deloitte office. Your technical prowess, including programming and ML modeling capabilities, will be evaluated against the finalized candidates throughout these interviews.
If you were assigned take-home exercises, you may also be invited to a presentation round during the on-site interview for the Machine Learning Engineer role at Deloitte.
What Questions Are Asked in a Deloitte Machine Learning Engineer Interview?
Typically, interviews at Deloitte vary by role and team, but commonly machine learning engineer interviews follow a fairly standardized process across these question topics.
A team wants to A/B test changes in a sign-up funnel, such as changing a button from red to blue and/or moving it from the top to the bottom of the page. How would you set up this test?
2. How would you forecast Facebook’s revenue for the next year?
An executive asks you to forecast Facebook’s revenue for the coming year. How would you approach this task?
3. How would you determine if a redesigned email campaign led to an increase in conversion rates?
An E-commerce store’s new-user to customer conversion rate increased from 40% to 43% after a new email journey was launched. However, the rate was 45% a few months prior. How would you investigate if the redesign caused the increase?
4. How would you ensure data quality across different ETL platforms for PayPal’s market research?
PayPal’s Southern African division uses multiple ETL pipelines to connect data marts with a survey platform’s data warehouses, including translation modules for text data. How would you ensure data quality across these platforms?
5. How would you conduct an experiment to test Uber’s ETA range feature?
A PM at Uber wants to test a new feature displaying ETA as a range (e.g., 3-7 minutes) instead of a direct estimate. How would you conduct this experiment and determine if the results are significant?
6. Write a SQL query to select the 2nd highest salary in the engineering department.
Write a SQL query to select the 2nd highest salary in the engineering department. If more than one person shares the highest salary, the query should select the next highest salary.
7. Determine the top 5 actions performed during the week of Thanksgiving and rank them.
Write a query to determine the top 5 actions performed during the week of Thanksgiving (11/22/2020 - 11/28/2020), and rank them based on the number of times performed. If two actions were performed equally, they should have the same rank.
8. Create a function precision_recall to calculate precision and recall metrics from a 2-D matrix.
Given a 2-D matrix P of predicted values and actual values, write a function precision_recall to calculate precision and recall metrics. Return the ordered pair (precision, recall).
9. Write a function to identify all duplicate values in a list of integers.
Identify all the duplicate values in the list given a list of integers. Assume that the list can contain both positive and negative numbers, and the order of the list does not matter. Return a list of the duplicate numbers.
10. Design three classes: text_editor, moving_text_editor, and smart_text_editor with specific functionalities.
Design three classes: text_editor, moving_text_editor, and smart_text_editor with specific functionalities. The text_editor class should have methods to write, delete, and get notes. The moving_text_editor class should extend text_editor and override the special_operation method to move the cursor. The smart_text_editor class should extend text_editor and override the special_operation method to serve as an undo operation.
11. What is the probability that it’s actually raining in Seattle given your friends’ responses?
You call 3 friends in Seattle, each with a 2⁄3 chance of telling the truth and a 1⁄3 chance of lying. All 3 say it is raining. Calculate the probability that it is actually raining.
12. What is the difference between Logistic and Linear Regression?
Explain the differences between Logistic and Linear Regression. When would you use one instead of the other in practice?
13. What will the regression coefficients be for Y on X and X on Y given Y = X + normal white noise?
Given two variables, X and Y, where Y = X + normal white noise: - What will the coefficient be if we run a regression of Y on X? - What happens if we run a regression of X on Y?
14. Which model would perform better for predicting Airbnb booking prices: linear regression or random forest regression?
You want to build a model to predict booking prices on Airbnb. Compare linear regression and random forest regression to determine which would perform better and explain why.
15. How would you tackle multicollinearity in multiple linear regression?
Describe the steps to address multicollinearity when performing multiple linear regression.
16. [What is the difference between logistic and linear regression? When would you use one instead of the other?(https://interviewquery.com/questions/linear-vs-logistic-regression)
Explain the differences between logistic and linear regression. Provide scenarios where each would be appropriately used in practice.
17. How would you build a “hot posts” or “trending posts” feature to increase engagement on Reddit?
The CEO of Reddit wants to increase overall engagement by creating a “hot posts” or “trending posts” sort feature. If you were leading this project, describe your approach to building this feature.
How to Prepare for a Machine Learning Engineer Interview at Deloitte
You should plan to brush up on any technical skills and try practicing machine learning interview questions and mock interviews as possible. A few tips for acing your Deloitte interview include:
Understand Deloitte’s Impact Areas: Deloitte emphasizes leveraging advanced analytics and cognitive technologies to solve problems. Be sure to describe how your work can contribute to these areas.
Showcase Your Cloud Expertise: Experience with AWS, Azure, or Google Cloud is crucial for the role. Ensure you can discuss your projects involving cloud platforms in detail.
Display a Collaborative Approach: Team collaboration is key at Deloitte’s Government and Public Services practice. Be prepared to talk about how you’ve effectively worked within a team setting.
FAQs
What is the average salary for a Machine Learning Engineer at Deloitte?
What qualifications are required for the Machine Learning Engineer position?
Candidates must hold a Bachelor’s degree and have an active TS/SCI security clearance. They should possess over 8 years of experience in machine learning, with at least 6 years in developing and deploying models in a production environment. Proficiency in programming languages like Python and libraries such as TensorFlow, PyTorch, or scikit-learn is essential, along with experience in major cloud platforms like AWS, Azure, or GCP.
What’s the work culture like at Deloitte?
Deloitte values a diverse, equitable, and inclusive culture that empowers individuals to contribute their unique perspectives. The company fosters an environment of collaboration and innovation, encouraging employees to bring creativity to solving complex client challenges. Deloitte promotes continuous professional growth through various learning and development opportunities.
Conclusion
The Machine Learning Engineer role at Deloitte offers a dynamic and rewarding opportunity to shape the future of data-driven solutions within the Government and Public Services sector. From developing and deploying sophisticated machine learning models to collaborating with a diverse and inclusive team, the work you’ll do here will have a lasting impact on communities and organizations.
For those interested in excelling and preparing for this role, it’s crucial to understand the interview process thoroughly. If you want more insights about the company, check out our main Deloitte Interview Guide, where we have covered other possible interview questions that could be asked. Additionally, we have specific guides for other roles, such as software engineer and data analyst, to give you a comprehensive view of Deloitte’s interview process across different positions.
Good luck with your interview!