Enverus is a prominent energy SaaS firm, providing critical insights and analytics for the energy sector. Renowned for its innovative platforms and solutions, Enverus supports energy operations, trading, and investment through robust data and analytics. As a Data Analyst at Enverus, you'll be at the heart of turning complex data into actionable insights that drive strategic decision-making. The role demands proficiency in data analysis, visualization, and statistical tools, with a focus on improving energy strategies and operations.

In this guide, Interview Query will walk you through the interview process for the Data Analyst position at Enverus, detailing common questions and offering crucial preparation tips. Let's dive in!

Submitting Your Application

The first step in the interview process for joining Enverus as a Data Analyst is to submit a compelling application that reflects your technical skills and interest in becoming part of their team. Whether you were contacted by an Enverus 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 that are most relevant to the role.

Recruiter/Hiring Manager Call Screening

If your CV happens to be among the shortlisted few, a recruiter from the Enverus Talent Acquisition Team will reach out to verify key details like your experiences and skill level. Behavioral questions may also be included in the screening process.

In some cases, the Enverus Data Analyst hiring manager may be 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 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 Enverus Data Analyst role is usually conducted virtually, including video conferencing and screen sharing. Questions in this 1-hour interview stage may revolve around Enverus's data systems, ETL pipelines, and SQL queries.

For the data analyst roles, take-home assignments regarding product metrics, analytics, and data visualization may be included. Apart from these, your proficiency in hypothesis testing, probability distributions, and machine learning fundamentals may also be assessed.

Depending on the seniority of the position, case studies and similar real-world 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 Enverus office. Your technical prowess, including programming and ML modeling capabilities, will be evaluated against other 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 Enverus.

Quick Tips For Enverus Data Analyst Interviews

• Understand the Energy Sector: Enverus operates within the energy sector; having a basic understanding of this industry can go a long way in helping you shine during the interview.
• Be Proficient in Data Tools: Make sure to sharpen your skills in SQL, data visualization tools, and any specific data libraries or languages listed in the job description.
• Show Your Analytical Skills: Be prepared to discuss past projects where you've used data analysis to drive decisions. Highlight your ability to deliver actionable insights from complex data sets.

Typically, interviews at Enverus 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.

• Write a function to merge two sorted lists into one sorted list. Given two sorted lists, write a function to merge them into one sorted list. Bonus: Determine the time complexity.

• Create a function missing_number to find the missing number in an array. You have an array of integers, nums of length n spanning 0 to n with one missing. Write a function missing_number that returns the missing number in the array. Complexity of (O(n)) required.

• 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 function to search for a target value in a rotated sorted array. Suppose an array sorted in ascending order is rotated at some pivot unknown to you beforehand. You are given a target value to search. If the value is in the array, return its index; otherwise, return -1. Bonus: Your algorithm's runtime complexity should be in the order of (O(\log n)).

• Would you suspect anything unusual about the A/B test results with 20 variants? Your manager ran an A/B test with 20 different variants and found one significant result. Would you consider this result suspicious?

• How would you set up an A/B test for button color and position changes? 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?

• What steps would you take if friend requests on Facebook are down 10%? A product manager at Facebook reports a 10% decrease in friend requests. What actions would you take to investigate and address this issue?

• Why might job applications be decreasing while job postings remain constant? You observe that the number of job postings per day has remained stable, but the number of applicants has been decreasing. What could be causing this trend?

• What are the drawbacks of the given student test score datasets, and how would you reformat them? You have data on student test scores in two different layouts. What are the drawbacks of these formats, and what changes would you make to improve their usefulness for analysis? Additionally, describe common issues in "messy" datasets.

• Is this a fair coin? You flip a coin 10 times, and it comes up tails 8 times and heads twice. Determine if the coin is fair based on this outcome.

• How do you write a function to calculate sample variance? Write a function that outputs the sample variance given a list of integers. Round the result to 2 decimal places. For example, given test_list = [6, 7, 3, 9, 10, 15], the function should return 13.89.

• Is there anything fishy about the A/B test results with 20 variants? Your manager ran an A/B test with 20 different variants and found one significant result. Evaluate if there is anything suspicious about these results.

• How do you find the median in a list with more than 50% repeating integers in O(1) time and space? Given a list of sorted integers where more than 50% of the list is comprised of the same repeating integer, write a function to return the median value in (O(1)) computational time and space. For example, given li = [1,2,2], the function should return 2.

• What are the drawbacks of the given student test score datasets, and how would you reformat them? You have data on student test scores in two different layouts. Identify the drawbacks of these layouts, suggest formatting changes to make the data more useful for analysis, and describe common problems seen in "messy" datasets.

• How would you evaluate the suitability and performance of a decision tree model for predicting loan repayment? You are tasked with building a decision tree model to predict if a borrower will repay a personal loan. How would you evaluate whether a decision tree is the correct model for this problem? If you proceed with the decision tree, how would you evaluate its performance before and after deployment?

• How does random forest generate the forest and why use it over logistic regression? Explain the process by which a random forest generates its forest. Additionally, discuss why one might choose random forest over other algorithms such as logistic regression.

• When would you use a bagging algorithm versus a boosting algorithm? Compare two machine learning algorithms. In which scenarios would you use a bagging algorithm versus a boosting algorithm? Provide examples of the tradeoffs between the two.

• How would you justify using a neural network model and explain its predictions to non-technical stakeholders? Your manager asks you to build a neural network model to solve a business problem. How would you justify the complexity of this model and explain its predictions to non-technical stakeholders?

• What metrics would you use to track the accuracy and validity of a spam classifier? You are tasked with building a spam classifier for emails and have completed a V1 of the model. What metrics would you use to track the accuracy and validity of the model?

If you're eager to dive into the dynamic world of data analytics at Enverus, make sure to explore our detailed Enverus Interview Guide. We've compiled a wealth of interview questions and insider insights to help you prepare effectively. Plus, you can find specialized guides for other roles, such as data analyst at Enverus, offering a deeper understanding of their interview process.

At Interview Query, we're dedicated to empowering you with the tools, knowledge, and confidence to excel in every Enverus interview challenge.

Check out all our company interview guides to enhance your preparation, and feel free to reach out with any questions.

Good luck with your interview!