Knewin is a cutting-edge technology company that helps organizations make informed strategic decisions through data-driven insights. As a leader in the data intelligence field, Knewin leverages advanced AI and machine learning technologies to provide comprehensive media monitoring, social listening, and market analysis solutions.

The Data Scientist position at Knewin is a dynamic role that involves utilizing advanced statistical techniques, machine learning algorithms, and data mining tasks to develop predictive models and extract meaningful insights from complex datasets. This position requires a PhD in Data Science, Computer Science, Statistics, Mathematics, or a related field. Candidates are expected to have strong programming skills, a track record of innovative problem-solving, and the ability to communicate complex technical concepts to non-technical stakeholders.

In this guide, we will walk you through the interview process, typical interview questions for the Data Scientist role at Knewin, and provide valuable tips to help you succeed. Let’s dive in!

Submitting Your Application

The initial step is to submit a compelling application that reflects your technical skills and interest in joining Knewin as a Data Scientist. Whether you were contacted by a Knewin recruiter or took the initiative yourself, carefully review the job description and tailor your CV according to the prerequisites.

Tailoring your CV may include identifying specific keywords that the hiring manager might use to filter resumes and crafting a targeted cover letter. Furthermore, don’t forget to highlight relevant skills and mention your work experiences.

Recruiter/Hiring Manager Call Screening

If your CV makes it to the shortlisted candidates, a recruiter from the Knewin Talent Acquisition Team will make contact and verify key details like your experiences and skill level. Behavioral questions may also be part of the screening process.

In some cases, the Knewin hiring manager might be present during the screening round to answer your queries about the role and the company itself. They may also engage in surface-level technical and behavioral discussions.

The recruiter call should take about 30 minutes.

Technical Virtual Interview

Successfully navigating the recruiter round will earn you an invitation for the technical screening round. This stage usually involves a virtual interview conducted via video conference and screen sharing. Questions in this 1-hour long interview may revolve around Knewin’s data systems, ETL pipelines, and SQL queries.

For Data Scientist roles, take-home assignments regarding predictive modeling, machine learning, and data mining tasks are often incorporated. Your proficiency in hypothesis testing, probability distributions, and machine learning fundamentals may also be assessed.

Depending on the seniority of the position, you might be assigned case studies and similar real-scenario problems.

Onsite Interview Rounds

Following a second recruiter call outlining the next stage, you’ll be invited to attend the onsite interview loop. During your day at the Knewin office, multiple interview rounds will be conducted, varying with the role. These interviews will evaluate your technical prowess, including programming and machine learning modeling capabilities.

If you were assigned take-home exercises, you may have to present your solutions during the onsite interview.

Quick Tips For Knewin Data Scientist Interviews

• Be Well-Versed in Data Science: Ensure you have a robust understanding of statistical methods, machine learning algorithms, and data manipulation techniques. Brush up on predictive modeling, data mining, and related fields.
• Showcase Real-World Applications: Provide examples of how you have applied your data science skills in real-world scenarios. Highlight any projects or roles that demonstrate your ability to derive insights from complex datasets.
• Prepare for Behavioral Questions: Be ready to discuss your past experiences, particularly those that exhibit your problem-solving skills, teamwork, and how you handle challenges. Tailor your responses to reflect Knewin’s core values and culture.

Typically, interviews at Knewin vary by role and team, but commonly Data Scientist interviews follow a fairly standardized process across these question topics.

• How would you measure the effectiveness of extra pay for delivery drivers during peak hours? You work at a food delivery company. How would you measure the effectiveness of giving extra pay to delivery drivers during peak hours to meet consumer demand?

• Create a function rain_days to calculate the probability of rain on the nth day after today. The probability that it will rain tomorrow depends on whether it rained today and yesterday. If it rained both days, there's a 20% chance it will rain tomorrow. If it rained one of the days, there's a 60% chance. If it rained neither day, there's a 20% chance. Given it rained today and yesterday, write a function to calculate the probability it will rain on the nth day after today.

• What are the assumptions of linear regression? List and explain the key assumptions that must be met for linear regression analysis to be valid.

If you want more insights about the company, check out our main Knewin Interview Guide, where we have covered many interview questions that could be asked. We’ve also created interview guides for other roles, such as software engineer and data analyst, where you can learn more about Knewin’s interview process for different positions.

At Interview Query, we empower you to unlock your interview prowess with a comprehensive toolkit, equipping you with the knowledge, confidence, and strategic guidance to conquer every Knewin data scientist interview questions and challenges.

You can check out all our company interview guides for better preparation, and if you have any questions, don’t hesitate to reach out to us.

Good luck with your interview!