The SAP data science interview consists of a multi-step process interview process. The first step is a technical live Skype coding screen. The data scientist interviewer will ask about your background and your past experience. Prepare a five-minute elevator pitch on past projects, your interest in data science, and why you want to work at SAP.
After reviewing the background and past projects, the interviewer will jump into a live coding exercise and problem. These SAP data scientist interview questions on the coding part will likely be in Python and done over Coderpad.
What do you want to achieve during your time at SAP? Please discuss both your short-term and long-term goals, and how they align with SAP's mission and your role as a Data Scientist.
When discussing your goals at SAP, articulate a clear vision of your career trajectory that aligns with the company's mission to 'help the world run better.' For short-term goals, focus on contributing to specific projects or products, such as enhancing SAP's cloud transformation efforts through innovative data science solutions. For long-term goals, express a desire to grow into leadership roles where you can guide teams in pioneering AI innovations. Emphasize how your personal growth will contribute to SAP's overall success and commitment to innovation.
Typically, interviews at SAP vary by role and team, but commonly Data Scientist interviews follow a fairly standardized process across these question topics.
The second phase of the SAP data science interview will be on-site. This will consist of one behavioral interview and three technical interviews. The technical interviews will span a process of white-boarding coding questions, SQL and data analysis and processing questions, and machine learning conceptual questions. Make sure to review general machine learning concepts and coding exercises.
An example SAP technical interview in machine learning would be going deep into two projects that an SAP data scientist is working on. The interviewer would describe two of their current projects and would brainstorm what techniques to improve model performance. Make sure to engage in a thoughtful discussion as this is how they measure how well they would work together with you.
We’ve gathered this data from parsing thousands of interview experiences sourced from members.
Let’s look at some examples of SAP data scientist interview questions.
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