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Automatic Data Processing (ADP) Data Analyst Interview Questions and Answers

Updated 13 Jun 2025

Automatic Data Processing (ADP) Data Analyst Interview Experiences

3 interviews found

Data Analyst Interview Questions & Answers

user image Anonymous

posted on 29 Dec 2024

Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Aptitude Test 

It is nice to do work

Round 2 - Aptitude Test 

It helps in understanding the 5

Round 3 - Coding Test 

It helps a lot in company

Round 4 - Technical 

(5 Questions)

  • Q1. How to do job in company?
  • Q2. What I should do?
  • Q3. How to do work?
  • Ans. 

    Effective work involves planning, execution, analysis, and continuous improvement to achieve goals efficiently.

    • Set clear goals: Define what you want to achieve, e.g., completing a project by a specific deadline.

    • Plan your tasks: Break down your work into manageable tasks, like creating a timeline for data analysis.

    • Prioritize: Focus on high-impact tasks first, such as analyzing key metrics that drive business decisions.

    • U...

  • Answered by AI
  • Q4. What should I do
  • Q5. What is the goal?
  • Ans. 

    The goal of a Data Analyst is to analyze data to extract valuable insights and make data-driven decisions.

    • Identify trends and patterns in data

    • Create visualizations to communicate findings

    • Provide actionable recommendations based on data analysis

  • Answered by AI

Data Analyst Interview Questions & Answers

user image Anonymous

posted on 13 Jun 2025

Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

I appeared for an interview before Jun 2024, where I was asked the following questions.

  • Q1. Talk about customer support
  • Q2. Excel knowledge

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Data Analyst Interview Questions & Answers

user image Anonymous

posted on 7 May 2024

Interview experience
2
Poor
Difficulty level
-
Process Duration
-
Result
-
Round 1 - HR 

(1 Question)

  • Q1. Some questions on background, why this role

Top trending discussions

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Interview Tips & Stories
2w
boredinlife
·
works at
Mercer
I left in the middle of an interview.
M a self-taught developer. been working really hard, trying to break into tech. Two days ago, I got approached by an hr from this e learning company for an IT role. I was super nervous but also excited because it felt like maybe this is it. The interview was on teams with 9 experienced pros all with degrees and certifications while I had no formal IT background, just self-taught skills. I felt completely out of place. Most of the interviewers were kind and said I could learn on the job. But one person kept throwing back-to-back questions with shady comments after every answer made me feel like I wasn’t good enough. It crushed my confidence About 10 minutes before the interview ended, I panicked. Anxiety took over, so I faked a network issue and left the call. Then I just broke down. I didn’t want to be disrespectful, so I quickly emailed saying I got disconnected. Truth is, I was overwhelmed and felt like a total fraud. I’ve wanted a job in tech for so long.
Got a question about Automatic Data Processing (ADP)?
Ask anonymously on communities.

Interview questions from similar companies

I applied via Recruitment Consultant and was interviewed in Jan 2021. There were 6 interview rounds.

Interview Questionnaire 

4 Questions

  • Q1. Basically they asked about data flow of my previous company.
  • Q2. Tableau and machine learning basics questions
  • Q3. Sql intermediate questions, but it answerable
  • Q4. Mostly they scheduled your interview with clients,in my case its 2 times with client. They asked about my understanding of data and how can I use my knowledge of data science in their domain and business c...

Interview Preparation Tips

Interview preparation tips for other job seekers - Be prepared with your basics and good understanding of data and domain
Interview experience
4
Good
Difficulty level
Moderate
Process Duration
4-6 weeks
Result
Not Selected

I applied via Naukri.com and was interviewed in Dec 2022. There were 4 interview rounds.

Round 1 - Resume Shortlist 
Pro Tip by AmbitionBox:
Keep your resume crisp and to the point. A recruiter looks at your resume for an average of 6 seconds, make sure to leave the best impression.
View all tips
Round 2 - Coding Test 

String Reverse Coding Test


User
Share Detail for coding test

ChatGPT
Certainly! I'd be happy to provide you with details for a coding test. Here's an example of a coding test description:

Title: String Reversal

Description:
Write a function that takes a string as input and returns the reverse of that string. The function should reverse the order of characters in the string and return the reversed string as the output.

Requirements:

The function should be named reverseString and take a single parameter, inputString, of type string.
The function should return a string.
The function should handle both uppercase and lowercase letters.
The function should preserve any whitespace or special characters in the input string.
The function should not use any built-in or library functions that directly solve this problem.
Example:
Input: "Hello, World!"
Output: "!dlroW ,olleH"

Note:

The input string can be of any length.
The input string may contain alphanumeric characters, whitespace, or special characters.
Evaluation Criteria:

Correctness of the solution.
Efficiency and clarity of the code.
Proper handling of edge cases and error conditions.
Adherence to coding best practices.
Please complete the task within 30 minutes and submit your solution as a single file. Feel free to use any programming language you are comfortable with.
Good luck!

Round 3 - Aptitude Test 

String Reverse Coding Test


User
Share Detail for coding test

ChatGPT
Certainly! I'd be happy to provide you with details for a coding test. Here's an example of a coding test description:

Title: String Reversal

Description:
Write a function that takes a string as input and returns the reverse of that string. The function should reverse the order of characters in the string and return the reversed string as the output.

Requirements:

The function should be named reverseString and take a single parameter, inputString, of type string.
The function should return a string.
The function should handle both uppercase and lowercase letters.
The function should preserve any whitespace or special characters in the input string.
The function should not use any built-in or library functions that directly solve this problem.
Example:
Input: "Hello, World!"
Output: "!dlroW ,olleH"

Note:

The input string can be of any length.
The input string may contain alphanumeric characters, whitespace, or special characters.
Evaluation Criteria:

Correctness of the solution.
Efficiency and clarity of the code.
Proper handling of edge cases and error conditions.
Adherence to coding best practices.
Please complete the task within 30 minutes and submit your solution as a single file. Feel free to use any programming language you are comfortable with. Good luck!





User
Share derail for amplitude test

ChatGPT
Certainly! Here's an example of a coding test description for an amplitude test:

Title: Finding Amplitude

Description:
Write a function that takes a list of integers as input and returns the amplitude of the list. The amplitude of a list is defined as the difference between the largest and smallest elements in the list.

Requirements:

The function should be named findAmplitude and take a single parameter, inputList, which is a list of integers.
The function should return an integer representing the amplitude of the input list.
The function should handle both positive and negative integers.
The function should handle an empty list as input and return 0 as the amplitude.
Example:
Input: [2, 5, 9, -1, 3, 7]
Output: 10

Explanation:
The largest element in the list is 9, and the smallest element is -1. Therefore, the amplitude is 9 - (-1) = 10.

Note:

The input list can contain duplicates.
The input list can be of any length.
Evaluation Criteria:

Correctness of the solution.
Efficiency and clarity of the code.
Proper handling of edge cases and error conditions.
Adherence to coding best practices.
Please complete the task within 30 minutes and submit your solution as a single file. Feel free to use any programming language you are comfortable with.
Good luck!

Round 4 - Group Discussion 

Certainly! Here's an example of a group discussion topic:

Topic: The Impact of Artificial Intelligence on the Job Market

Description:
In this group discussion, we will explore the impact of artificial intelligence (AI) on the job market. AI is rapidly advancing, and its integration into various industries and sectors has raised concerns about the future of work.

Points to consider:
Potential job displacement: Discuss how AI has the potential to automate tasks and replace human jobs in various fields. Explore which industries or job roles are most susceptible to automation and the potential consequences for workers.

Job creation: Explore the other side of the argument and discuss how AI can also create new job opportunities. Consider the emergence of AI-related roles such as data scientists, AI trainers, and AI ethicists. Discuss the skills and expertise required for these new job roles.

Skills and education: Discuss the importance of skills development and education in adapting to the changing job market. Explore what skills will be in high demand in an AI-driven economy and how individuals and organizations can upskill or reskill to remain relevant.

Ethical considerations: Consider the ethical implications of AI in the job market. Discuss issues such as algorithmic bias, data privacy, and the responsibility of companies and policymakers in ensuring a fair and inclusive job market.

Job market transformation: Discuss the overall transformation of the job market due to AI. Explore how AI is reshaping traditional job roles, the gig economy, and the potential for new forms of work, such as remote work and flexible arrangements.

Guidelines:

Each participant should express their thoughts and ideas clearly and respectfully.
Encourage active listening and give everyone an opportunity to speak.
Support your arguments with relevant examples or data, if possible.
Be open to different perspectives and engage in constructive debate.
Evaluation Criteria:

Clarity of thought and expression.
Ability to articulate and support arguments.
Active participation and engagement with other participants.
Respectful and collaborative attitude towards the group discussion.
Please prepare your thoughts on the topic before the discussion. The group discussion will last for approximately 30 minutes. Good luck!

Interview Preparation Tips

Interview preparation tips for other job seekers - As a data science job seeker, here are some key pieces of advice to help you in your job search:

Develop a Strong Foundation: Ensure you have a solid understanding of the fundamental concepts and techniques in data science. This includes knowledge of statistics, mathematics, programming (Python and R are commonly used), machine learning algorithms, and data manipulation.

Build a Portfolio: Create a portfolio that showcases your data science skills and projects. This could include personal projects, Kaggle competition entries, or contributions to open-source projects. A portfolio demonstrates your practical experience and can set you apart from other candidates.

Gain Practical Experience: Seek out opportunities to work on real-world data science problems. Consider internships, freelance projects, or collaborations with researchers or companies. Practical experience not only enhances your skills but also demonstrates your ability to apply your knowledge to solve real problems.

Stay Updated: Keep up with the latest developments in the field of data science. Follow blogs, participate in online forums and communities, and attend conferences or webinars. Being aware of emerging technologies, techniques, and trends shows your dedication to continuous learning and growth.

Network: Build connections within the data science community. Attend industry events, join professional organizations, and engage with professionals through social media platforms like LinkedIn and Twitter. Networking can lead to valuable job opportunities, referrals, and insights into the industry.

Customize Your Applications: Tailor your resume and cover letter for each job application. Highlight relevant skills, projects, and experiences that align with the specific requirements of the position. A personalized application shows your attention to detail and genuine interest in the role.

Prepare for Interviews: Be prepared for technical interviews that assess your data science skills. Practice coding exercises, algorithmic problem-solving, and be able to explain your projects in a clear and concise manner. Additionally, be prepared to answer behavioral and situational questions to demonstrate your problem-solving, teamwork, and communication skills.

Continuously Learn and Improve: Data science is a rapidly evolving field, so embrace a growth mindset. Seek opportunities to learn new techniques, explore new domains, and expand your skill set. Take online courses, attend workshops, or pursue advanced degrees if necessary. Show that you are committed to staying ahead of the curve.

Emphasize Communication Skills: Data scientists are not just expected to analyze data but also effectively communicate their findings to non-technical stakeholders. Develop your ability to present complex concepts in a clear and concise manner, both verbally and in written form. Strong communication skills will make you a valuable asset to any organization.

Be Persistent and Resilient: The job search process can be challenging and may require time and perseverance. Don't get discouraged by rejection or setbacks. Learn from each experience, seek feedback, and continuously refine your approach. With persistence and a positive attitude, you'll increase your chances of landing a data science job.

Remember, the field of data science is highly competitive, so it's important to stand out from the crowd. By following these tips and continuously improving your skills, you can increase your chances of securing a rewarding job in data science. Good luck with your job search!

Interview Questionnaire 

2 Questions

  • Q1. About data science
  • Q2. What is used and where is used
  • Ans. 

    Data is used in various industries and sectors for analysis and decision-making.

    • Data is used in finance to analyze market trends and make investment decisions.

    • Data is used in healthcare to track patient outcomes and improve treatment plans.

    • Data is used in marketing to analyze customer behavior and target advertising campaigns.

    • Data is used in transportation to optimize routes and improve logistics.

    • Data is used in educat...

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers -
I advised that ask only leveling questions. And they freshers then don't ask high type questions it to be only working level questions

Skills evaluated in this interview

Interview experience
5
Excellent
Difficulty level
Hard
Process Duration
Less than 2 weeks
Result
No response

I applied via Walk-in and was interviewed in Mar 2024. There was 1 interview round.

Round 1 - One-on-one 

(2 Questions)

  • Q1. Introduction about our self
  • Ans. 

    I am a data analyst with 5 years of experience in analyzing and interpreting complex data sets to drive business decisions.

    • I have a strong background in statistical analysis and data visualization techniques.

    • Proficient in SQL, Python, and Tableau for data manipulation and reporting.

    • Experience in developing predictive models and conducting A/B testing to optimize marketing strategies.

  • Answered by AI
  • Q2. Complete discussion about projects

Interview Preparation Tips

Interview preparation tips for other job seekers - prepaire well
Are these interview questions helpful?
Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
-
Result
No response
Round 1 - Technical 

(2 Questions)

  • Q1. What is difference between rank and dense rank?
  • Ans. 

    Rank assigns unique ranks to each distinct value, while dense rank does not leave gaps between ranks.

    • Rank assigns consecutive integers to each distinct value based on their order.

    • Dense rank also assigns consecutive integers, but does not leave gaps between ranks.

    • For example, if we have values 10, 20, 20, 30, then rank would be 1, 2, 2, 4 and dense rank would be 1, 2, 2, 3.

  • Answered by AI
  • Q2. What is RLS in Power Bi?
Round 2 - Behavioral 

(1 Question)

  • Q1. How would you identify time for any project?
  • Ans. 

    Identifying time for a project involves creating a timeline, setting deadlines, and monitoring progress.

    • Create a project timeline outlining key milestones and tasks

    • Set deadlines for each task to ensure timely completion

    • Monitor progress regularly to identify any delays and adjust timelines accordingly

  • Answered by AI
Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Not Selected

I applied via Campus Placement and was interviewed in Sep 2023. There was 1 interview round.

Round 1 - Case Study 

KPI's for the ecommerce industries

Interview Preparation Tips

Interview preparation tips for other job seekers - Prepare SQL Questions, product based questions, adobe analytics, excel questions

I appeared for an interview in Jan 2022.

Round 1 - Technical 

(2 Questions)

  • Q1. Dense rank and row number differenxw
  • Ans. 

    Difference between dense rank and row number

    • Dense rank assigns the same rank to ties, while row number assigns a unique rank to each row

    • Dense rank skips ranks when there are ties, while row number does not

    • Dense rank is used to calculate percentiles, while row number is used for pagination

  • Answered by AI
  • Q2. Sql and nosql diff? Python functions

Interview Preparation Tips

Interview preparation tips for other job seekers - Read sql and practice well with some good python

Skills evaluated in this interview

Automatic Data Processing (ADP) Interview FAQs

How many rounds are there in Automatic Data Processing (ADP) Data Analyst interview?
Automatic Data Processing (ADP) interview process usually has 2-3 rounds. The most common rounds in the Automatic Data Processing (ADP) interview process are Aptitude Test, HR and Coding Test.
How to prepare for Automatic Data Processing (ADP) Data Analyst interview?
Go through your CV in detail and study all the technologies mentioned in your CV. Prepare at least two technologies or languages in depth if you are appearing for a technical interview at Automatic Data Processing (ADP). The most common topics and skills that interviewers at Automatic Data Processing (ADP) expect are Equity, Agile, Analytical skills, Business Intelligence and Compliance.
What are the top questions asked in Automatic Data Processing (ADP) Data Analyst interview?

Some of the top questions asked at the Automatic Data Processing (ADP) Data Analyst interview -

  1. How to do wo...read more
  2. What is the go...read more
  3. Talk about customer supp...read more

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Overall Interview Experience Rating

3/5

based on 4 interview experiences

Difficulty level

Moderate 100%

Duration

Less than 2 weeks 50%
2-4 weeks 50%
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Automatic Data Processing (ADP) Data Analyst Salary
based on 47 salaries
₹2.9 L/yr - ₹11.4 L/yr
13% more than the average Data Analyst Salary in India
View more details

Automatic Data Processing (ADP) Data Analyst Reviews and Ratings

based on 8 reviews

2.9/5

Rating in categories

3.0

Skill development

3.2

Work-life balance

3.4

Salary

2.8

Job security

3.1

Company culture

2.7

Promotions

3.0

Work satisfaction

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