Accenture is a global professional services company with a strong presence in India, renowned for its comprehensive range of services including strategy, consulting, digital, technology, and operations. Accenture collaborates with clients to help them become high-performance businesses, leveraging the full spectrum of their capabilities.

For the Product Analyst position, Accenture seeks individuals who can bridge the gap between technical and business teams, utilizing skills in data analysis, product management, and user experience. This role involves working closely with stakeholders to define product requirements, analyze market trends, and ensure successful product launches.

If you're aiming to join Accenture as a Product Analyst, this guide is tailored for you. We’ll walk you through the interview process, commonly asked questions, and tips to ace your interview. With Interview Query, you’ll get insights to help you prepare effectively. Let’s dive in!

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining Accenture as a Product Analyst. Whether you were contacted by an Accenture 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 Accenture 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 Accenture product 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 Accenture product analyst role is usually conducted through virtual means, including video conference and screen sharing. Questions in this 1-hour long interview stage may revolve around Accenture’s data systems, ETL pipelines, and SQL queries.

In the case of product 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 Accenture 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 product analyst role at Accenture.

Quick Tips For Accenture Product 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 Accenture interview include:

• Know Your Accenture Products and Services: Accenture questions are standardized and rely heavily on situational scenarios with their products and services. Study Accenture’s large breadth of services and understand how you would personally improve or test them.
• Be Data Driven: Accenture’s data science and product 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.
• Embrace the Consulting Mindset: Accenture values innovation, client-centric solutions, and collaboration. Practice responding to behavioral questions with answers that touch on Accenture’s core values.

Typically, interviews at Accenture In India vary by role and team, but commonly Product 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.

• Create a function to find the maximum number in a list of integers. Given a list of integers, write a function that returns the maximum number in the list. If the list is empty, return None.

• Create a function convert_to_bst to convert a sorted list into a balanced binary tree. Given a sorted list, create a function convert_to_bst that converts the list into a balanced binary tree. The output binary tree should have a height difference of at most one between the left and right subtrees of all nodes.

• Write a function to simulate drawing balls from a jar. 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 a list called n_balls.

• Develop a function can_shift to check if one string can be shifted to become another. Given two strings A and B, write a function can_shift to return whether or not A can be shifted some number of places to get B.

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

• How would you locate a mouse in a 4x4 grid using the fewest 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. Describe a strategy to find the mouse using the fewest number of scans.

• How would you select Dashers for Doordash deliveries in NYC and Charlotte? Doordash is launching delivery services in NYC and Charlotte and needs a process for selecting dashers. Describe how you would decide which dashers to select and whether the criteria would be the same for both cities.

• What factors could bias Jetco's study on boarding times? Jetco, a new airline, had a study showing it has the fastest average boarding times. Identify factors that could have biased this result and what you would investigate further.

• How would you design an A/B test to evaluate a pricing increase for a B2B SAAS company? A B2B SAAS company wants to test different subscription pricing levels. Describe how you would design a two-week A/B test to evaluate a pricing increase and determine if it is a good business decision.

• How much should a ride-sharing app budget for a $5 coupon initiative? A ride-sharing app has a probability (p) of dispensing a $5 coupon to a rider and services (N) riders. Calculate the total budget needed for the coupon initiative.

• What is the probability of riders getting a coupon? A driver using the app picks up two passengers. Determine:

• The probability of both riders getting the coupon.

• The probability that only one of them will get the coupon.

• What is a confidence interval for a statistic and why is it useful? Explain what a confidence interval is, why it is useful to know, and how to calculate it.

• What is the probability of finding an item on Amazon's website? Amazon has a warehouse system where items are located at different distribution centers. Given the probabilities that item X is available at warehouse A (0.6) or warehouse B (0.8), calculate the probability that item X would be found on Amazon's website.

• Is a coin fair if it comes up tails 8 times out of 10 flips? You flip a coin 10 times, and it comes up tails 8 times and heads twice. Determine if this coin is fair.

• What are time series models and why are they needed? Describe what time series models are and explain why they are necessary when less complicated regression models exist.

• How would you justify the complexity of building a neural network model and explain 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?

• How would you evaluate and deploy 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 if a decision tree is the correct model? 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 how random forest generates its forest. Additionally, why would you choose random forest over other algorithms like logistic regression?

• How would you explain linear regression to a child, a college student, and a mathematician? Explain the concept of linear regression to three different audiences: a child, a first-year college student, and a seasoned mathematician. Tailor your explanations to each audience's understanding level.

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

Step into the dynamic world of Accenture in India as a Product Analyst, and experience the excitement and challenges this role has to offer. If you’re eager to gain more insights about Accenture in India, check out our main Accenture Interview Guide, where you'll find numerous interview questions that might come your way. We’ve also crafted detailed interview guides for other roles such as software engineer and data analyst, providing a thorough look into different interview processes at Accenture in India.

At Interview Query, we give you the tools to enhance your interview skills with a comprehensive toolkit, arming you with the knowledge, confidence, and strategic advice to tackle every challenge during your Product Analyst interview at Accenture in India.

Check out all our company interview guides for comprehensive preparation. If you have any questions, don’t hesitate to reach out to us.

Good luck with your interview!