Mastercard Data Scientist Interview Questions

In this post, I'm going to share the interview experience for a data scientist position at Mastercard. Overall, the overall process is quite fast and efficient. 

Human Resource 

First, there was no HR round, and an HR communicated with me directly via email asking relevant questions such as:

• Current base salary and other perks
• Notification period
• Expected salary 
• Hybrid arrangement and if I'm OK with that 
• ...

Technical Round

Then the HR scheduled the first round, which is a 1 hour session with three people for checking technical skills. There was no pair-coding session, and it was mainly organized as a set of questions from each of the three interviewers. 

• Asked simple SQL and python questions and to talk about the solutions
• Questions regarding ML basics
• Tech stack match between the post and my experience
• ...

After a few days, I got a call from the HR and checked my availability and fixed the interview time of the next round. It seems their internal process is quite fast.

Hiring manager round

The second (and final) round is a 45 minute session with the hiring manager and one principle individual contributor (IC). Overall, they would like to know if I could jump into the role to execute the new upcoming project.

• Details about current role
• Experience of leading (how many) people 
• Practical experience of deploying ML in real-world settings
• The scale of previous projects (e.g., how many end users, data scale)
• How you would like to start structure the ML project?
• What is the north star and how did you deliver?
• ...

The final notification regarding the decision was also out quite quickly, on weekend as I recall. 

Overall, the interview process of Mastercard is quite efficient and fast, and jump directly into tech details and testing match between the post and candidate. I hope this post is helpful for you in case you are preparing a similar position for Mastercard. 

DocuSign Machine Learning Engineer Questions

In this post, I will share the interview experience for a DocuSign Machine Learning Engineer (MLE) post regarding the first round followed by the CV screening.

The first round is a technical screening by a lead MLE, and the round is about one hour long, and includes three parts:

• Elaborating details on ML projects 
• ML questions
• Coding

The first part is about discussing one or two ML projects in your CV in detail. Based on your description, the interviewer can ask some detailed questions with respect to the project.

The second part is about a set of ML questions regarding NLP and deep learning, as DocuSign's main product is focused on NLP. Some questions regarding LLMs can also be expected given the current NLP trends.

Finally, it is coding session, which is typical leetcode-like one to solve a coding problem in the given time.

Hope it helps if you are interviewing similar posts at DocuSign!

Huawei Data Science Interview Questions

This post is about the interview experience for a data scientist position at Huawei IRC (Irish Research Centre). As part of Huawei Europe, IRC mainly focuses on other markets except Asian ones such as China, South Korea, and Japan, and is trying to solve business problems such as Ad optimization on those markets.

Regarding the job post, an agency contacted me regarding the position and I only went through one hiring manager round and stopped. So this post is mainly about the interview questions with the hiring manager (HM). 

The HM round is a 1 HR interview consists of the following structure.

• 5 min: introduction of each
• 10 min: presentation about your previous experience
• 15 min: Q&A regarding the specifications about the job post
• 25 min: code pairing (Leetcode-like, messed up this)
• 5 min: ask any questions regarding the role

Some questions mentioned during the interview are:

• Some questions related to the presentation.
• What is your contribution/role in a specific project? I think it is mainly trying to figure out your part exactly if there are many team members or authors in a paper.
• What is the current state-of-the-art for the problem?
• What are some impressive papers you have read recently regarding the specific area of the job post?
• Regarding the project of job post related questions, e.g., if you do xxx., how will you approach or provide solutions

Overall, the interview process is well organized, and the interviewer is kind despite of the messing up for the code paring section. 

Optum Data Scientist Interview Questions

This post is about an interview experience for a data scientist position at Optum. It could be useful if you are going through or having one upcoming for a similar position at Optum or UnitedHealth Group. 

Optum, Inc. is an American healthcare services provider with business interests encompassing technology and related services, pharmacy care services and various direct healthcare services. It has been a subsidiary of UnitedHealth Group since 2011. And Optum seems to contribute the biggest portion of the UnitedHealth's profits, and has been growing very fast in the past years.

After submitting the CV for the position, I got a call from HR to arrange the interview, and there are two rounds of interview in total:

• technical interview
• behavior interview

Technical interview

The interview consists of two data scientists - one principle and one senior. 

Followed by a brief introduction about each, there was a project description section to describe a data science project has been done in your previous work experience. And there will be some questions delving into the details based on the project description you gave. 

The second part was about a mock project simulation, which has no right or wrong answer, but rather to understand how your thinking process works when you starting a new data science project. And there can be some questions based on your answers as well.

Finally, there can be a couple of technical questions related to data science and machine learning. It seems the interviewers have prepared a set of questions need to be covered. 

At the end, there can be some time for you to ask a couple of questions regarding the position and the company. Overall, the people look nice and friendly during the interview, and the interview difficulty is reasonable.

The interviewers were gentle and kind. However, the feedback process seems not satisfactory. After  more than 10 days, there was no feedback and no update on the job dashboard and I inquired about the feedback of the interview. An HR person said there will be updates and they will get back to me, but it turns out there is no update at the end and after a while I found the job board status is also silently changed to "No longer under consideration" without sending a rejection email.

Yahoo Research Scientiest Interview Questions

The interview process is structured as follows:

• HR screening interview (30 min)
• Manager/Priciple Scientist screening interview (1 hr)
• Research Talk/Presentation (1 hr)
• Technical Interview (1 hr) x 4 panels

HR screening interview is straighforward. Didn't ask those behavior questions, instead, it was more focused on describing the role and expectations and skills required, and your status for joining if succeed, e.g., visa status, when to start etc.

Manager or principle (in my case) screening interview lasted for 1 hour. Basically technical questions and research related questions based on your resume. Questions might related to their projects ongoing or related to your projects or papers before. For example, in my case,

• what activation fuctions you use for multilabel classification?
• what are the evaluation metrics you have used in your research paper? what is the difference between mAP and nDCG (when to use which?)

Then they will invite you for a rearch talk - 1 hr session - with a group of audience in the large research team in addition to your interview panels (4-5 people). The talk topic can be anything such as your thesis topic or about your recent papers.

Afterwards, there will be 4 rounds of technical interviews (1 hr for each) with interview panel members. Each member will ask technical questions based on which research area your position belonging to. In case of ML, questions can be quite vary such as:

• what's the statistical assumption behind logistic regresstion?
• what's the relationship between dropout and l2 regularization?
• why we don't initialize weights of parameters as zeros?
• what optimizers have you used and describe those

In addition to those technical questions, the interview session also includes open questions regarding their previous or ongoing projects, such as:

• how to design entity recommendation system from start to end?
• how to design a system to recommend trending topics? how to extract trending terms?

Overall, the interview process is well arranged with the HR and the feedback loop is quick fast, and the panel members were quite nice and friendly. 

NOKIA Bell Labs Research Scientist Interview Questions

The interview structure for a research scientist was structured as follows:

• HR interview
• 1-hour research talk
• Interviews with the HEADs of other departments (30 mins each)
• Interview with my hiring manager's manager (30 mins)
• CTO / the president of Bell Labs (Marcus Weldon, 30 mins)
• 2 interviews with potential team mates (30 mins each)

HR interview was normal one - similar to other HR interviews - asking about current status, possible starting date, and visa status, etc.

1-hour research talk / presentation is also common for traditional research labs such as IBM or Yahoo where you gave a presenation regarding your PhD or any topics of your interests, followed by questions from all the audience. Normally the audience can be anyone of the bigger research group where the hiring team has sent out the group invitations for attending the talk.

All the other interviews with management levels are more related to recent research and your research area, and some questions related to your research questions, thesis, future directions etc. Nothing particularly difficult as it is about your research.

The other interviews with team mates are more about discussion of current projects and ask your approaches for those problems, in addition to some general  ML questions such as what is SGD, etc.

Overall the process is quite organized, all the interviewers are friendly and provided comfortable interview environment, and I got the feedback after 1-2 weeks.

Maynooth University Lecturer Interview Questions

This is an interview experience for a lecturer job post for Maynooth University. The interview lasts for 30-40 minutes with 10 minute presentation for a choosen research topic followed by questions from 5 committees where two of them from other Universities. 

Teaching Related Questions

• How to do deal with several hundreds of students sitting there without any reaction while you teaching?
• How to do interact with those hudreds of students during the class?
• What is the target students when you design a course with difficulty level?
• How do you transfer European Pedagogy to the university in China?
• How do you assure the quality of teaching courses?
• What does your research do with deep learning and symbolic AI?
• How do you feel living in different coutries six months each year?
• How do you develop your research career while having heavy teaching loads?

Research Related Questions

• What do you see AI development in the future?
• What kind of funding can your research bring?
• How do you plan to recruit PhD students for the research?

The overall environment is very friendly and conformtable. After the interview, the Head of Department walked together with me to outside of the building.

Questions to prepare for academic job interviews

This post summarizes a list of questions that can be asked in your academic job interviews. If you are already passed the CV screening process and landed to an interview, it is already a great progress as you might be in the limited number of candidates out of hundreds of applicants. 

On top of your great progress so far, the interview normally aims to find out whether you are a good "FIT" of the job post that you have applied, and whether you are a good colleague, mentor, and teacher that the University is looking for with a set of prepared questions with a limited time. Therefore, we need to try to meet the requirements that the interviewers looking for with short and neat answers.

Interview is indeed a nervous situation, but remember, it is also a situation with new opportunities, and, it is OK to be not perfect.

In the following, we have a set of curated interview questions that might be useful to think of and prepare before your interviews, which are categorized into four aspects below:

• General questions
• Teaching related questions
• Research related questions
• Questions related to admin duties

General questions

• Introduce yourself 
• Why are you excited about the position?
• Why you choose to apply our institution?
• Describe the skills you have that will make you a good lecturer?
• How do you organize your day?
• When are you available to start? 

Teaching

• Your teaching philosophy 
• What’s your teaching style as a Lecturer? Tell us about your teaching style
• Describe the skills you have that will make you a good lecturer?
• What can you teach? What would you like to teach? What do you want to teach?
• What experiences do you have working with and teaching diverse students?
• Do you think you have diverse teaching experience?
• How do you feel about teaching other foundamental courses that might out of your expertise?
• If you design the degree, what kind of modules will be there to construct it?
• What do students say about your teaching?
• Tell me what you like and dislike about teaching, and in particular, being a University lecturer?
• What is the difference or relationship between traditional algorithms and ML algorithms?
• Tell us how you deal with a classroom of students with different abilities and levels of motivation?
• How do you deal with developing a new course?
• What types of projects can students do in your group?
• What are your thoughts on technology in the classroom?
• Tell me what you like and dislike about teaching, and in particular, being a University lecturer?
• How will you deal with less motivated students?
• How do you deal with disruptive students in the classroom?
• Share some specific successes and failures in the classroom
• If you could develop a new course, what would it be?
• What is your teaching related experience?
• What is your supervision related experience?
• What is the difficult part for you during educational experience? 
• What did you learn about it?
• What is your opinion about online/offline learning?
• What is your opinion about assessment formats such as assignments and final term exam styles?
• What are the final exam covers that assignments do not cover?
• What have you learned about our student body that excites you/concerns you?
• If you are teaching 3 courses and a faculty member comes to say if you can teach 4th one for help due to an emergency? What will you do?

Research

• What kind of research metrics do you think is the best for evaluating a faculty, e.g., h-index or impact factors?
• How do you select good PhD candidates?
• What is your approach to mentoring?
• Understanding of national funding landscape
• What types of fundings you would like to apply for your research
• How do you choose the venues to submit for your research
• What are top venues that you didn't make it but would like to have in the future
• What is your top paper and why, what is the impact / What do you think are your most significant research accomplishments?
• What do you consider to be your best paper/work and why? What are your most important publications? What are the two best papers of yours?
• What did it change about the way people approach the field?
• What has been the impact of your research?
• Who here might you collaborate with?
• What are the resources will you need to be successful? 
• What papers do you have coming through in the next year?
• What is the status of the grant you listed on your CV?
• How will you excite students about your research?
• What do you see in 10 years? Where is your research heading in the next 5-10 years?
• What new techniques/approaches will you be developing?
• What is innovative about your research? 
• How is your work distinct from your supervisor’s/principal investigator’s? How intellectually independent are you? How will you distinguish yourself from your mentor?
• What influences have you been exposed to?  Who has influenced you the most?
• Do you think you have enough breadth of experience?
• What has been your role so far in developing research ideas and carrying them forward?
• If we gave you the position, what might go wrong? How will you manage the risks?

Admin duties 

• What kind of admin duties are you aware of and would like to contribute? What department/school committee work interests you?
• What kind of admin duties have you contributed to?
• What do you know about our University’s EDI policies

In this post, we have summarized a list of interview questions for those who are seeking academic jobs with respect to general, teaching, research, and admin duties. Hope the list will have you to some extent with your faculty job search.

If you have other interesting questions worth to mention during your academic job interviews that might be helpful for others, please also leave a comment below.

Amazon Research Scientist Phone Interview Questions

I had a chance to got the phone interview for a research scientist role in Amazon UK (research for Alexa) before PhD gragudation. After the initial CV application, a HR person contacted me and scheduled for an interview with a researcher in the team that I've applied.

Overall, the interview process took 30 mins, and the questions are based on my research area and really delved into details to see how I describe/deliver concepts to non-technical people as well as some research questions about my research topics.


Some questions: 

• Describe CNN
• Why CNN in terms of fully connected NN
• Describe LSTM
• Why LSTM solves the vanishing gradient problem
• Why word embeddings reveal the semantic relationships (man:king- woman:queen)
• coding, there is a stream of numbers, how to find a pair of a and b which sum up to x? (failed)

Summary:

• Too much focused on the preparation of Amazon Principles, which the interviewer did not ask.
• Lack of preparation of coding
• Too nervous for the first job interview...