PWC Data Analyst Interview Questions + Guide in 2024

PWC Data Analyst Interview Questions + Guide in 2024

Overview

PwC is a global professional services network renowned for its excellent consulting, tax, and assurance services. It provides significant impact through industry-leading expertise and innovative solutions, helping clients navigate the evolving business landscape.

As a data analyst candidate at PWC, you are expected to handle diverse tasks including data management, business intelligence, and solving complex analytical problems.

In this guide, we will help you understand the interview process, common PWC data analyst interview questions, and preparation tips.

What Is the Interview Process Like for a Data Analyst Role at PWC?

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining PwC as a data analyst. Whether you were contacted by a PwC 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 PwC Talent Acquisition Team will make contact and verify key details like your experiences and skill level. Behavioral interview questions may also be a part of the screening process.

In some cases, the PwC 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 PwC 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 PwC’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

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 day at the PwC 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 PwC.

What Questions Are Asked in a PWC Data Analyst Interview?

Typically, interviews at PWC vary by role and team, but data analyst interviews follow a fairly standardized process across these question topics.

1. How would you assess the validity of the result in an AB test with a .04 p-value?

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

2. What kind of analysis would you conduct to recommend changes to the UI?

You have access to tables summarizing user event data for a community forum app. Conduct a user journey analysis using this data to recommend improvements to the user interface.

3. How would you determine how much Spotify should pay for an ad in a third-party app?

As a data scientist on Spotify’s marketing team, how would you calculate the appropriate amount Spotify should pay for an advertisement in a third-party app?

4. How would you debug and improve the efficiency of a slow SQL query?

You are running a SQL query that is taking a long time. How would you determine if it’s taking too long, and what steps would you take to debug and improve its efficiency?

5. Write a SQL query to select the 2nd highest salary in the engineering department.

Note: If more than one person shares the highest salary, the query should select the next highest salary.

Example:

Input:

employees table

Column Type
id INTEGER
first_name VARCHAR
last_name VARCHAR
salary INTEGER
department_id INTEGER

departments table

Column Type
id INTEGER
name VARCHAR

Output:

Column Type
salary INTEGER

6. How can PG&E model the electricity supply needed for a town?

PG&E needs to forecast the exact amount of electricity to supply a town to avoid outages and waste. What is one way to model the required electricity supply?

7. How can we model the electricity supply for a town to avoid outages and waste?

PG&E needs to forecast the exact amount of electricity to supply a town each year. The goal is to avoid outages from under-supply and waste from over-supply. What is one way to model this?

8. How do sentiment analysis models convert raw text data into numerical vectors and get trained?

To perform sentiment analysis on an Amazon customer feedback dataset, you need to convert raw text data into numerical vectors. Explain how these models work and how they are trained.

9. How would you assess the effectiveness of a clustering model for grouping similar basketball players without pre-labeled data?

You are hired by the LA Lakers to scout potential players and group them based on their strengths and weaknesses. After training a clustering model, how would you evaluate if it successfully grouped similar players without having pre-labeled data?

How to Prepare for a Data Analyst Interview at PWC

Here are some quick tips to prepare for your PWC data analyst interview:

  • Prepare Technically: Technical interviews at PwC emphasize SQL queries, data systems, and programming using Python. Review your fundamentals and practice thoroughly.
  • Case Studies: PwC often uses case studies to evaluate problem-solving skills in a real-world context. Be prepared to discuss and solve case-based questions.
  • Behavioral Fit: Demonstrate your alignment with PwC’s core values and competency models. Use the STAR (Situation, Task, Action, Result) method to structure your responses in behavioral interviews.

FAQs

What is the average salary for a Data Analyst at Pwc?

We don't have enough data points to render this information. Submit your salary and get access to thousands of salaries and interviews.

What technical skills are important for the Data Analyst position at PwC?

Knowledge of programming languages like Python and its libraries, such as NumPy and Pandas, is crucial. Proficiency in SQL is also highly valued, along with hands-on experience in machine learning and data analysis tools. Understanding business intelligence tools like Tableau or Power BI can also be beneficial.

What is the company culture like at PwC?

PwC has a culture that emphasizes professional development, teamwork, and a values-driven approach. The firm encourages continuous learning and provides various opportunities for career progression. Employee experiences often highlight the collaborative and supportive environment within the company.

Conclusion

Applying for a data analyst position at PwC involves a multi-faceted, challenging, and thorough interview process designed to uncover the best talent, and we hope this interview guide is a great addition to your interview prep.

If you want more insights about the company, check out our main PwC Interview Guide, where we have covered other interview questions that could be asked as well.

Good luck with your interview!