What is CI/CD pipeline and what is customer segmentation?
Lead Data Scientist Interviews
Lead Data Scientist Interview Questions
"As a lead data scientist, you will be responsible for developing creative and effective improvements to a company's product by analyzing data from consumers, websites, sales, and many other sources. During an interview, expect to be given many case studies about what information you can draw from a particular set of data as well as to be tested on your general statistical and computer science knowledge. A background in computer science, statistics, or another related field is required. "
398 lead data scientist interview questions shared by candidates
How much are getting paid now?
What is your take on competitor strategy in terms of Machine Learning?
For this position, most of the questions were directed towards management skill and philosophy. Only few technical questions, possibly because of my academic background and my similar roles.
Why cant you stay in one profession
Asked about experience in Time Series Algorithms
They sent a link to some publicly-available data and told me to tell them something interesting about it.
1: Trees-based methods are sometimes called greedy algorithms. Can you explain what greedy means, and then explain what is a potential downside of using a greedy algorithm? 2) Can you explain the concept of multicollinearity and how it can impact a model? Then discuss how you measure the amount of multicollinearity. Finally, using the measure you identified, how much multicollinearity would cause concern for a model, and why? 3) A colleague approaches you with an idea to run a marketing mailer experiment. The colleague wants to test the impact of two different marketing mailers (let’s call them Mailer A and Mailer B) on life insurance sign-ups. The colleague asks you: “how many mailers do I need to send out to have a statistically significant sample?” How do you respond? What questions would you ask the colleague to help answer their question? 4) Assume you deployed a binary classification model and after 12 months your business partner asks you to verify the model is still performing as expected. What steps would you take to validate the deployed model’s performance? What different recommendations would you give your business partner if the model is performing as expected versus if the model is showing deteriorated performance? 5) Please share what you like about the open role. 6) Can you tell us about your prior mentoring or leadership experiences? 7) why statefarm .
What is your ideal job?
Case studies related to MPL problems like recommendation systems, fraud detection etc
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