Protege is a cutting-edge tech company that specializes in providing innovative solutions to help businesses achieve growth and operational efficiency. Known for its dynamic work environment and forward-thinking approach, Protege attracts top talent looking to make a significant impact in the tech industry.

Stepping into the role of a Data Analyst at Protege is a rewarding challenge. This role demands proficiency in data manipulation, statistical analysis, and data visualization tools. As a Data Analyst, you'll delve into large datasets to uncover insights that drive strategic decisions and improve company performance.

If you're gearing up to join this innovative company, our guide on Interview Query is designed for you. In this guide, we’ll navigate through the interview process, share commonly asked questions for the Data Analyst position at Protege, and provide valuable tips to help you succeed. Let’s get started!

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining Protege as a data analyst. Whether you were contacted by a Protege 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 Protege 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 Protege 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 Protege 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 Protege’s 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

Following 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 day at the Protege office. 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 Protege.

Quick Tips For Protege Data Analyst Interviews

• Should contain three tips for interviewing for this specific company based on interview experiences.

Example:

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 Protege interview include:

• Know Your Protege Products: Protege questions are standardized and rely heavily on situational scenarios with their products. Study Protege’s large breadth of products and understand how you would personally improve or test them.
• Be Data Driven: Protege’s data analyst interviews assess how well you can provide business-driving insights with data science. Brush up on your knowledge of statistics and probability, given these questions can be some of the hardest to solve.
• Embody the Spirit: Protege at its core has a collaborative, employee-focused culture that values innovation. Practice responding to behavioral questions with answers that touch on Protege’s core values.

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

• Write a SQL query to select the 2nd highest salary in the engineering department. Write a SQL query to select the 2nd highest salary in the engineering department. If more than one person shares the highest salary, the query should select the next highest salary.

• Develop a function precision_recall to calculate precision and recall metrics from a 2-D matrix. Given a 2-D matrix P of predicted values and actual values, write a function precision_recall to calculate precision and recall metrics. Return the ordered pair (precision, recall).

• Write a SQL query to select the top 3 departments with at least ten employees and rank them by the percentage of employees making over 100K. Given employees and departments tables, select the top 3 departments with at least ten employees and rank them according to the percentage of their employees making over 100K in salary.

• Create a function traverse_count to determine the number of paths in an (n \times n) grid. Given an integer (n), write a function traverse_count to determine the number of paths from the top left corner of an (n \times n) grid to the bottom right. You may only move right or down.

• Develop a function is_subsequence to check if one string is a subsequence of another. Given two strings, string1 and string2, write a function is_subsequence to find out if string1 is a subsequence of string2. A subsequence can be derived by deleting some elements without changing the order of the remaining elements.

• What considerations should be made when testing hundreds of hypotheses with many t-tests? When testing hundreds of hypotheses using multiple t-tests, what factors should you consider to ensure the validity and reliability of your results?

• How does random forest generate the forest and why use it over logistic regression? Explain how random forest generates multiple decision trees and why it might be preferred over logistic regression for certain tasks.

• How do we handle missing square footage data in Seattle housing price predictions? You have 100K sold listings over three years with 20% missing square footage data. Describe methods to handle this missing data to construct a predictive model.

• How would you combat overfitting in tree-based classification models? When training a classification model, explain strategies to prevent overfitting, particularly in tree-based models.

• Does increasing the number of trees in a random forest always improve accuracy? Discuss whether sequentially increasing the number of trees in a random forest model will continuously improve its accuracy.

• How would you implement k-means clustering in Python from scratch? Given a two-dimensional NumPy array data_points, number of clusters k, and initial centroids, write a Python function to perform k-means clustering and return the cluster assignment for each data point.

• How would you explain what a p-value is to someone who is not technical? Explain the concept of a p-value in simple terms to a non-technical person. Use analogies or everyday examples to make it understandable.

• How should you handle a right-skewed distribution when predicting real estate home prices? You are building a model to predict home prices in a city and notice the prices are right-skewed. Determine if any action is needed and what steps to take. Bonus: What should you do if the target distribution is heavily left-skewed instead?

Optimize your preparation for the Data Analyst role at Protege with our specialized resources. If you want more insights about the company, check out our main Protege 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 Protege’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 Protege 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!