Help Scout is dedicated to helping businesses delight their customers, operating with over 12,000 companies since 2011. As a fully remote team of 140+ people spread across the globe, Help Scout emphasizes a balance between profit and purpose. Since 2019, they have been a Certified B Corporation, pledging 1% of equity back to the community.

Joining Help Scout as a Data Analyst involves working closely with executives and leadership to measure success, track business health, and discover data-backed opportunities for growth. You'll engage in data storytelling, collaborate with leadership to shape strategy, and foster a data-driven culture. If you're passionate about data and making a meaningful impact, this guide will walk you through the interview process and common questions you might encounter. Visit Interview Query for comprehensive interview preparation insights.

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining Help Scout as a Data Analyst. Whether you were contacted by a 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 Help Scout's 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 Help Scout data analyst 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 Virtual Interview

Successfully navigating the recruiter round will present you with an invitation for the technical screening round. Technical screening for the Help Scout data analyst role usually is conducted through virtual means, including video conference and screen sharing. Questions in this 1-hour long interview stage may revolve around data systems, ETL pipelines, and SQL queries.

In the case of data analyst roles, take-home assignments regarding product metrics, analytics, and data visualization are incorporated. Apart from these, your proficiency against hypothesis testing, probability distributions, and machine learning fundamentals may also be assessed during the round.

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

Onsite Interview Rounds

Followed by a second recruiter call outlining the next stage, you’ll be invited to attend the onsite interview loop. Multiple interview rounds, varying with the role, will be conducted during your time with Help Scout. Your technical prowess, including programming and ML modeling capabilities, will be evaluated against the finalized candidates throughout these interviews.

If you were assigned take-home exercises, a presentation round may also await you during the onsite interview for the data analyst role at Help Scout.

Quick Tips for Help Scout Data Analyst Interviews

You should plan to brush up on any technical skills and try as many practice interview questions and mock interviews as possible. A few tips for acing your Help Scout interview include:

• Know the Company Values: Help Scout emphasizes their core values heavily. Be prepared to situate your answers within their value framework, highlighting instances where your prior experiences align with values like "Happy to Help," "Craft over Convention," and "Own the Outcome."
• Demonstrate Data Storytelling Expertise: Help Scout values the ability to use data to narrate compelling stories. Brush up on your skills in data visualization tools and practice translating complex data insights into understandable narratives.
• Collaboration and Communication: Given the remote nature of Help Scout, strong collaboration and communication skills are essential. Highlight your experience in working successfully in distributed teams and your ability to communicate effectively.

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

• How would you set up an A/B test to optimize button color and position for higher click-through rates? A team wants to A/B test changes in a sign-up funnel, such as changing a button from red to blue and/or moving it from the top to the bottom of the page. How would you design this test?

• Would you suspect anything unusual if an A/B test with 20 variants shows one significant result? Your manager ran an A/B test with 20 different variants and found one significant result. Would you find this result suspicious?

• Why might the average number of comments per user decrease despite user growth in a new city? A social media company launched in a new city and saw a slow decrease in the average number of comments per user from January to March, despite consistent user growth. What could be the reasons, and what metrics would you investigate?

• What metrics would you use to determine the value of each marketing channel for a B2B company? Given all the different marketing channels and their respective costs for a company selling B2B analytics dashboards, what metrics would you use to assess the value of each channel?

• How would you locate a mouse in a 4x4 grid using the fewest number of scans? You have a 4x4 grid with a mouse trapped in one of the cells. You can "scan" subsets of cells to know if the mouse is within that subset. How would you determine the mouse's location using the fewest scans?

• Write a function called find_bigrams to return a list of all bigrams in a sentence or paragraph. Write a function called find_bigrams that takes a sentence or paragraph of strings and returns a list of all its bigrams in order. A bigram is a pair of consecutive words.

• Write a query to get the last transaction for each day from a table of bank transactions. Given a table of bank transactions with columns id, transaction_value, and created_at, write a query to get the last transaction for each day. The output should include the id, datetime, and transaction amount, ordered by datetime.

• Write a function find_change to find the minimum number of coins for a given amount of change. Write a function find_change to find the minimum number of coins that make up the given amount of change cents. Assume we only have coins of value 1, 5, 10, and 25 cents.

• Write a function to simulate drawing balls from a jar based on their counts. Write a function to simulate drawing balls from a jar. The colors of the balls are stored in a list named jar, with corresponding counts of the balls stored in the same index in a list called n_balls.

• Write a function calculate_rmse to calculate the root mean squared error of a regression model. Write a function calculate_rmse to calculate the root mean squared error of a regression model. The function should take in two lists, one that represents the predictions y_pred and another with the target values y_true.

• What is the expected number of good ads rated by 100 raters independently? Given 80% of raters are careful and 20% are lazy, calculate the expected number of good ads when 100 raters each rate one ad independently.

• What is the expected number of good ads rated by one rater for 100 ads? Given 80% of raters are careful and 20% are lazy, calculate the expected number of good ads when one rater rates 100 ads.

• What is the probability that a rater was lazy if an ad is rated as bad? Given 80% of raters are careful and 20% are lazy, calculate the probability that a rater was lazy if an ad is rated as bad.

• How to simulate coin tosses with a given probability of heads? Write a function that takes the number of tosses and the probability of heads, returning a list of randomly generated results ('H' for heads, 'T' for tails).

• How to calculate the sample variance of a list of integers? Write a function that takes a list of integers and returns the sample variance, rounded to 2 decimal places.

• What is the probability of rolling at least one 3 with 2 dice? Calculate the probability of rolling at least one 3 when rolling 2 dice.

• What is the probability of rolling at least one 3 with (N) dice? Calculate the probability of rolling at least one 3 when rolling (N) dice.

• What is the probability of finding an item on Amazon's website given its availability in two warehouses? Given the probabilities that an item is available at warehouse A (0.6) and warehouse B (0.8), calculate the probability that the item would be found on Amazon's website.

• What kind of model did the co-worker develop for loan approval? Your co-worker developed a model that takes customer inputs and returns if a loan should be given or not. Identify the type of model used.

• How would you measure the difference between two credit risk models? Given that personal loans are monthly installments, how would you compare the performance of two credit risk models over a specific timeframe?

• What metrics would you track to measure the success of the new credit risk model? Identify the key metrics to track in order to measure the success of a new credit risk model for personal loans.

• What metrics would you use to track the accuracy and validity of a spam classifier model? Assume you have built a V1 of a spam classifier for emails. Specify the metrics you would use to evaluate its accuracy and validity.

• What are the key differences between classification models and regression models? Explain the main differences between classification models and regression models.

• When would you use a bagging algorithm versus a boosting algorithm? Compare two machine learning algorithms and provide an example of the tradeoffs between using a bagging algorithm and a boosting algorithm.

• What would happen when you run logistic regression on perfectly linearly separable data? Describe the outcome of running logistic regression on a dataset that is perfectly linearly separable.

What is the average salary for a Data Analyst at Help Scout?

Q: What is Help Scout’s mission and company culture like?
Help Scout is on a mission to help businesses delight more customers through outstanding customer support. We've been fully remote since 2011 and value balance between profit and purpose, becoming a Certified B Corporation in 2019. Our culture emphasizes accountability, empathy, and high standards, with core values like "Happy to Help," "Craft over Convention," "Progress not Perfection," and "Own the Outcome."

Q: What are the primary responsibilities of a Data Analyst at Help Scout?
As a Data Analyst at Help Scout, you’ll work closely with leadership to define success metrics, track business health, and uncover data-backed growth opportunities. You’ll be responsible for data storytelling, developing a data and analysis roadmap, collaborating with engineers for product development, and fostering a data-driven culture through training and resources.

Q: What skills and experience are required for the Data Analyst role?
We look for candidates with 4+ years of experience with SQL, data warehousing, BI tools like Looker or Tableau, and a strong interest in statistical analysis. Experience with large datasets, data modeling, and a background in project management are also important. Collaboration and effective communication skills are essential for working with various teams.

Q: What is the compensation and benefits package for the Data Analyst role?
The salary range for this role is $136,000 - $147,000. Help Scout offers a robust perks and benefits package including healthcare coverage, wellness resources, and more. We follow a remote compensation philosophy and pay the same irrespective of geographic location.

Q: What should candidates know about the hiring guidelines at Help Scout?
Our roles are fully remote, but some carry specific location-based eligibility requirements. We currently hire from the US, Canada, Australia, Finland, Ireland, Netherlands, Poland, UK, Denmark, Germany, and Norway. We do not sponsor visas, so you must be authorized to work from your home location. We're committed to diversity and inclusion and provide accommodations during the recruitment process if needed.

If you want more insights about the company, check out our main Help Scout 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 Help Scout’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 Help Scout Data Analyst interview question and challenge.

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!