Interview Guide Overview

Grammarly is a leading AI-powered writing assistance company trusted by over 30 million people and 70,000 professional teams daily. Known for its innovation in communication enhancement, Grammarly offers a hybrid remote-working model, fostering a dynamic and collaborative culture.

Position Overview

The Data Scientist role at Grammarly is critical in driving the company's growth and product strategy. Ideal candidates will have substantial technical and analytical expertise, alongside strong problem-solving and communication skills. The interview process at Grammarly is thorough, featuring multiple stages, including recruiter calls, technical assessments, case studies, and virtual onsite interviews. Candidates will interact with various team members, reflecting Grammarly's collaborative and inclusive culture.

Prepare with Interview Query's resources to excel in your interview process and secure a meaningful role at Grammarly.

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining Grammarly as a Data Scientist. Whether you were contacted by a Grammarly recruiter or have taken 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 happens to be among the shortlisted few, a recruiter from the Grammarly Talent Acquisition Team will make contact and verify key details like your experiences and skill level. Behavioral questions may also be a part of the screening process.

In some cases, the Grammarly Data Scientist hiring manager stays present during the screening round to answer your queries about the role and the company itself. They may also indulge in surface-level technical and behavioral discussions.

The whole recruiter call should take about 30 minutes.

Technical Take-Home Assignment

After successfully navigating the recruiter round, you'll be presented with a take-home technical assignment. This assignment generally involves open-ended questions that require thorough analysis and careful thought. Typically, you will need to spend several hours completing this task, demonstrating your analytical skills, proficiency with tools such as Python or SQL, and your ability to offer actionable insights from your findings.

Virtual Onsite Interview Rounds

Following the review of the take-home assignment, if successful, you will be invited to attend the virtual onsite interview. Multiple interview rounds, varying with the role, will be conducted. During the virtual onsite, expect to engage in technical interviews, experiment design, and product case study discussions.

Moreover, the interview process includes value interviews where your professional values and cultural fit within Grammarly are assessed. The virtual onsite is designed to gauge your overall technical capabilities, problem-solving skills, and alignment with Grammarly’s values.

Quick Tips For Grammarly Data Scientist Interviews

1. Understand Grammarly’s Products and Market Position:

   • Familiarize yourself with Grammarly’s range of products and how they leverage AI to assist in writing. This understanding will help frame your answers in context to the company's domain.

2. Focus on Data-Driven Insights:

   • Grammarly values the ability to derive actionable insights from data. Brush up on your knowledge of statistical analysis, A/B testing, and machine learning techniques as these are critical areas in their interview process.

3. Align with Grammarly’s Core Values:

   • Grammarly emphasizes a culture that is ethical, adaptable, gritty, empathetic, and remarkable (EAGER). Prepare to answer behavioral questions demonstrating how you embody these values in your professional life.

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

• How would you assess the validity of the AB test result with a .04 p-value? Your company is running a standard control and variant AB test on a feature to increase conversion rates on the landing page. The PM checks the results and finds a .04 p-value. How would you assess the validity of this result?

• How would you differentiate between scrapers and real people in a dataset of page views? Given a dataset of page views where each row represents one page view, how would you differentiate between scrapers and real people?

• Why did the treatment group with $10 rewards have a lower response rate than the control group? You designed an experiment to measure the impact of financial rewards on users’ response rates. The treatment group with $10 rewards has a 30% response rate, while the control group without rewards has a 50% response rate. Can you explain what happened and how you could improve this experimental design?

• How would you test the close friends feature on Instagram Stories while accounting for network effects? You want to test the close friends feature on Instagram Stories. How would you create a control group and a test group to account for network effects?

• Create a function to find the length of the largest palindrome that can be made from a string's characters.

• How would you explain the impact of financial rewards on users' response rates and improve the experimental design? You designed an experiment to measure the impact of financial rewards on users' response rates. The treatment group with $10 rewards had a 30% response rate, while the control group without rewards had a 50% response rate. Explain the results and suggest improvements for the experimental design.

• How would you explain linear regression to a child, a first-year college student, and a seasoned mathematician? Explain the concept of linear regression to three different audiences: a child, a first-year college student, and a seasoned mathematician, tailoring each explanation to their understanding level.

• What happens when you run logistic regression on perfectly linearly separable data? Given a dataset of perfectly linearly separable data, describe the outcome of running logistic regression on it.

• How would you evaluate and validate a decision tree model for predicting loan repayment? As a data scientist at a bank, you need to build a decision tree model to predict loan repayment. Explain how you would evaluate if a decision tree is the right model and how you would assess its performance before and after deployment.

• How would you justify using a neural network model to non-technical stakeholders? If tasked with building a neural network model to solve a business problem, explain how you would justify the model's complexity and explain its predictions to non-technical stakeholders.

• How does random forest generate the forest, and why use it over logistic regression? Describe the process by which random forest generates its forest and explain why it might be preferred over other algorithms like logistic regression.

What is the average salary for a Data Scientist at Grammarly?

Q: What is the interview process like for a Data Scientist position at Grammarly?

A: The interview process at Grammarly typically includes an initial recruiter call, a technical take-home assignment, followed by a virtual onsite interview consisting of technical problems, case studies, and behavioral interviews. This process is designed to assess your technical skills, problem-solving abilities, and cultural fit. Candidates often describe the process as thorough, professional, and supportive.

Q: What kind of technical skills and experience are required for the Data Scientist role?

A: Grammarly looks for candidates with strong analytical and critical thinking skills, proficiency in programming languages such as SQL, Python, R, or Scala, and practical experience in data analysis, statistics, and machine learning. A Master’s degree in a quantitative field and at least 3-5 years of relevant work experience are typically required. Experience in experiment design, and statistical analysis is highly valued.

Q: What makes Grammarly's work environment and culture unique?

A: Grammarly operates under a remote-first hybrid model, allowing team members the flexibility to work primarily remotely with in-person collaboration a few weeks every quarter. The company values creativity, collaboration, and innovation, reinforced through its EAGER (ethical, adaptable, gritty, empathetic, and remarkable) values. Grammarly also supports professional growth, offers a connected team culture, and has comprehensive benefits.

Q: How can I best prepare for an interview at Grammarly?

A: Preparation for an interview at Grammarly should include practicing common data science problems, refining your technical skills, and understanding experiment design and statistical methodologies. Using resources such as Interview Query to solve relevant case studies and technical questions can be very effective for your preparation.

Q: What does Grammarly offer in terms of career and personal growth?

A: Grammarly provides extensive support for professional development through training, coaching, and regular feedback. The company fosters a connected team environment with various employee resource groups and programs celebrating accomplishments and promoting connection. Grammarly offers a competitive compensation package, including excellent health care benefits, 401(k) matching, ample paid time off, and various stipends for home office, wellness, and even pet care.

Ready to take the next step? Click here to start your journey with Interview Query.

Conclusion

Grammarly's Data Scientist position offers an unparalleled opportunity to work with a team that embodies professionalism, kindness, and a commitment to a collaborative and welcoming environment. The interview process, although thorough and multi-staged, is designed to ensure a mutual fit and to give candidates a real feel of the company's vibrant culture. The remote-first hybrid working model provides the flexibility to work from various locations while fostering in-person collaboration.

If you're ambitious, innovative, and eager to be a part of an industry leader in AI communication assistance, then the Data Scientist role at Grammarly might be your perfect fit. With a supportive team and a culture that encourages growth and learning, you'll have the platform to become a key player in shaping the future of communication.

For more insights about Grammarly and their interview process, check out our Grammarly Interview Guide, where we cover potential interview questions and detailed guides for various roles such as software engineer and data analyst.

At Interview Query, we provide you with the tools and knowledge to excel in your interview journey. Unlock your potential and gather the strategic insights needed to ace your interview.

Good luck with your interview!