Getting ready for an Data Scientist interview at NTT DATA? The NTT DATA Data Scientist interview span across 10 to 12 different question topics. In preparing for the interview:
Interview Query regularly analyzes interview experience data, and we've used that data to produce this guide, with sample interview questions and an overview of the NTT DATA Data Scientist interview.
How would you approach a project where you are required to work with imbalanced data? Please provide a specific example from your experience or a hypothetical scenario where you had to apply techniques to handle this issue.
When faced with imbalanced data, it is crucial to recognize the potential bias it can introduce into the model. My approach begins with understanding the distribution of classes and the implications of this imbalance on model performance. I would employ techniques such as resampling (over-sampling the minority class or under-sampling the majority class) and implementing different performance metrics (like precision, recall, and F1-score) to evaluate the model effectively. For example, in a previous project, I dealt with a healthcare dataset where positive cases were significantly fewer than negative cases. I used SMOTE (Synthetic Minority Over-sampling Technique) to create synthetic samples and improved recall from 60% to 85%, allowing for better identification of critical cases.
Describe a time when you had to present your data science project to a non-technical audience. What strategies did you use to ensure your message was understood?
When presenting to a non-technical audience, I focus on storytelling and visual aids. I start by outlining the problem and its significance, followed by a high-level overview of the solution without delving into technical jargon. For example, while presenting a predictive model for customer churn, I used visualizations to illustrate key insights and outcomes. I engaged the audience by asking questions and encouraging interaction, which helped in making the presentation more relatable. The feedback was positive, and several stakeholders mentioned they felt more informed and equipped to make decisions based on the insights I presented.
Can you provide an example of how you collaborated with a team on a data science project? What was your role, and how did you contribute to the team’s success?
In a recent team project focused on developing a recommendation system, I collaborated closely with data engineers and UX designers. My role involved data analysis and model training. I initiated weekly stand-up meetings to ensure everyone was aligned on progress and challenges. I also took the lead in integrating feedback from the UX team to refine our model’s outputs. This collaboration resulted in a system that improved user engagement by 30%. I learned the value of clear communication and the importance of integrating diverse perspectives in achieving project goals.
Typically, interviews at NTT DATA vary by role and team, but commonly Data Scientist interviews follow a fairly standardized process across these question topics.
We've gathered this data from parsing thousands of interview experiences sourced from members.
Practice for the NTT DATA Data Scientist interview with these recently asked interview questions.