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

Updated 29 Dec 2024

Automatic Data Processing (ADP) Data Analyst Interview Experiences for Experienced

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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?
  • 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

Interview questions from similar companies

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 3 interview rounds.

Round 1 - 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 2 - 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 3 - 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!

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
5
Excellent
Difficulty level
Moderate
Process Duration
4-6 weeks
Result
Selected Selected

I applied via Company Website and was interviewed in Jul 2024. There were 5 interview rounds.

Round 1 - One-on-one 

(1 Question)

  • Q1. Basic ml related questions,past project discussion
Round 2 - One-on-one 

(1 Question)

  • Q1. AI, ML related, statistical analysis of the graph.
Round 3 - Behavioral 

(1 Question)

  • Q1. Work culture, check
Round 4 - cross functional lob 

(1 Question)

  • Q1. Work culture, project discussion, scenario based questions
Round 5 - HR 

(1 Question)

  • Q1. Basic HR questions, why sap salary discussions
Interview experience
4
Good
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Selected Selected

I applied via Referral and was interviewed in Feb 2024. There were 5 interview rounds.

Round 1 - HR 

(2 Questions)

  • Q1. Self-introduction
  • Q2. What are your roles and responsibilities in current organization
  • Ans. 

    I am responsible for analyzing data, creating reports, and providing insights to support decision-making.

    • Analyze large datasets to identify trends and patterns

    • Create reports and dashboards to visualize data for stakeholders

    • Provide insights and recommendations based on data analysis

    • Collaborate with cross-functional teams to drive data-driven decision-making

  • Answered by AI
Round 2 - One-on-one 

(2 Questions)

  • Q1. Self-introduction
  • Q2. Brief discussion about the roles and responsibilities for current opening
  • Ans. 

    Lead Data Analyst oversees data analysis team, develops strategies, interprets data, and presents insights to stakeholders.

    • Manage and lead a team of data analysts

    • Develop data analysis strategies and methodologies

    • Interpret data and provide actionable insights to stakeholders

    • Collaborate with cross-functional teams to drive data-driven decision making

    • Ensure data quality and accuracy in analysis

    • Stay updated on industry tre

  • Answered by AI
Round 3 - Technical 

(3 Questions)

  • Q1. Self-introduction
  • Q2. Technical round for Python, SQL, Tableau and Advanced Excel
  • Q3. Scenario based questions
Round 4 - One-on-one 

(3 Questions)

  • Q1. Self-Introduction
  • Q2. What do you understand about Sales Comp and its roles and responsibilities
  • Ans. 

    Sales Comp is a system that determines how salespeople are compensated based on their performance.

    • Sales Comp is short for Sales Compensation

    • It involves designing and implementing a system to reward salespeople based on their sales performance

    • Roles include setting sales targets, determining commission structures, and monitoring sales performance

    • Responsibilities include analyzing sales data, calculating commissions, and ...

  • Answered by AI
  • Q3. Scenario based questions
Round 5 - One-on-one 

(2 Questions)

  • Q1. Self-introduction
  • Q2. Scenario based questions

Interview Preparation Tips

Topics to prepare for Salesforce Lead Data Analyst interview:
  • Sales comp
  • Data Analysis
  • Python
  • SQL
  • Tableau
  • Advanced Excel
  • CRM
Interview preparation tips for other job seekers - Before going to interview, first thoroughly read about the roles and responsibilities. Make yourself prepared accordingly.

Ask questions to the interviewer to understand their expectations for the role you are applying for.

Do some research about the company and the pay scale for your roles and put your expectations accordingly.
Interview experience
4
Good
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Coding Test 

Factorial coding questions and SQL coding questions using group by

Round 2 - Technical 

(2 Questions)

  • Q1. Java questions on oops concepts
  • Q2. SQL questions on having clause
Round 3 - HR 

(2 Questions)

  • Q1. Can you relocate
  • Q2. Brief info about amdocs
  • Ans. 

    Amdocs is a software and services provider for communications, media, and entertainment industries.

    • Founded in 1982 in Israel

    • Headquartered in Chesterfield, Missouri

    • Provides customer experience solutions for telecom companies

    • Offers services such as billing, CRM, and data analytics

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Stick to your resume and final year project
Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Coding Test 

45 mins.

questions based on basic string manipulation but not a straightforward task

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

(2 Questions)

  • Q1. Basic pandas questions on dataframes
  • Q2. Some quiz questions
Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
Round 1 - One-on-one 

(2 Questions)

  • Q1. Explain Decision Trees
  • Ans. 

    Decision Trees are a popular machine learning algorithm used for classification and regression tasks.

    • Decision Trees are a tree-like structure where each internal node represents a feature or attribute, each branch represents a decision rule, and each leaf node represents the outcome.

    • They are easy to interpret and visualize, making them popular for exploratory data analysis.

    • Decision Trees can handle both numerical and c...

  • Answered by AI
  • Q2. How will you finetune LLMs
  • Ans. 

    LLMs can be finetuned by adjusting hyperparameters, training on specific datasets, and using techniques like transfer learning.

    • Adjust hyperparameters such as learning rate, batch size, and number of layers to improve performance.

    • Train the LLM on domain-specific datasets to improve its understanding of specialized language.

    • Utilize transfer learning by starting with a pre-trained LLM model and fine-tuning it on a smaller...

  • Answered by AI

Skills evaluated in this interview

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

Automatic Data Processing (ADP) Interview FAQs

How many rounds are there in Automatic Data Processing (ADP) Data Analyst interview for experienced candidates?
Automatic Data Processing (ADP) interview process for experienced candidates usually has 4 rounds. The most common rounds in the Automatic Data Processing (ADP) interview process for experienced candidates are Aptitude Test, Coding Test and Technical.
How to prepare for Automatic Data Processing (ADP) Data Analyst interview for experienced candidates?
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 for experienced candidates?

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

  1. What is the go...read more
  2. How to do wo...read more

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Automatic Data Processing (ADP) Data Analyst Salary
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₹2.9 L/yr - ₹9.1 L/yr
At par with the average Data Analyst Salary in India
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4.6/5

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5.0

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4.8

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4.6

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