KPMG Data Scientist Interview Guide
Overview
Getting ready for an Data Scientist interview at KPMG? The KPMG Data Scientist interview span across 10 to 12 different question topics. In preparing for the interview:
- Know what skills are necessary for KPMG Data Scientist roles.
- Gain insights into the Data Scientist interview process at KPMG.
- Practice real KPMG Data Scientist interview questions.
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 KPMG Data Scientist interview.
KPMG Data Scientist Salary
Average Base Salary
Average Total Compensation
Cultural and Behavioral Questions
This feature is currently experimental, and we’re committed to improving it with your valuable feedback.Can you describe a challenging data analysis project you worked on? What steps did you take to overcome obstacles, and what was the outcome?
When discussing a challenging data analysis project, focus on the specific problem, the methodologies you used, and the results achieved. For instance, I worked on a project analyzing customer behavior data where the dataset was incomplete and noisy. I started by performing thorough data cleaning and preprocessing, using techniques like outlier detection and imputing missing values. I then applied exploratory data analysis (EDA) to identify patterns and gain insights. By collaborating with domain experts, I developed a predictive model that increased customer retention rates by 15%. This experience taught me the importance of perseverance and collaboration when facing data challenges.
Can you provide an example of a project where you collaborated with a cross-functional team? How did you ensure effective communication and teamwork?
When discussing collaboration, focus on your role, the team's dynamics, and the project's success. For example, during a project to develop a machine learning model, I worked closely with data engineers and product managers. I facilitated regular meetings to align our goals and update each other on progress. By using collaborative tools and clear documentation, we streamlined our communication. The project was successful, resulting in a model that improved product recommendations by 20%. This experience reinforced my belief in the power of teamwork and open communication.
Tell me about a time when project requirements changed unexpectedly. How did you handle it?
In situations where project requirements change, it's crucial to remain flexible and proactive. For instance, I was working on a data modeling project when the scope shifted due to new business insights. I organized a meeting with stakeholders to discuss the changes and their implications. I then adjusted our project timeline and reallocated resources to meet the new goals. This adaptability led to the successful completion of the project, which provided more relevant insights to the business. This experience highlighted the importance of agility in project management.
KPMG Data Scientist Interview Process
Typically, interviews at KPMG 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.
KPMG Data Scientist Interview Questions
Practice for the KPMG Data Scientist interview with these recently asked interview questions.