Binmile Interview Questions, Process, and Tips

Q1. - Performance Optimasion In React.
Ans. 
Performance optimization in React involves minimizing render cycles, reducing unnecessary re-renders, and optimizing component lifecycles.
• Use shouldComponentUpdate or React.memo to prevent unnecessary re-renders.

• Avoid binding functions in render method to prevent creating new function instances on each render.

• Use PureComponent for class components to perform shallow comparison of props and state.

• Implement lazy loading ...read more
Answered by AI
Add your answer
Q2. - Given an array we have to transform it differently.
Ans. 
Transform array of strings in a different way
• Iterate through the array and apply the transformation logic

• Consider using map or forEach method for transformation

• Example: Transform each string to uppercase
Answered by AI
Add your answer

Q1. - They generally asked for ORM and then asked me how internally ORM is able to switch to raw query
Add your answer

Q1. Question on knowledge of microservices, js basic questions and about database connection string.
Add your answer
Q2. A dsa question(easy)
Add your answer

Q1. Talked about projects, backend architecture, circular linked list, nosql vs sql.
Add your answer
Q2. Also asked why leaving previous company, if given different stack or work timings are not suitable for u.
Add your answer

Q1. Discussion with ceo asked college, and what are u scared of in life, what other thing u are scared of (stupid question), I said I might not keep growing and learning and his third question was why be scare...read more
Add your answer

Q1. Can you introduce yourself?
Ans. 
I am a data research executive with a background in statistics and experience in analyzing large datasets.
• Background in statistics

• Experience in analyzing large datasets

• Proficient in data research tools like Python, R, and SQL
Answered by AI
Add your answer
Q2. Can you provide a brief explanation of the job role and its responsibilities?
Ans. 
Data Research Executive is responsible for collecting, analyzing, and interpreting data to help organizations make informed decisions.
• Collecting data from various sources such as surveys, interviews, and databases

• Analyzing data using statistical software to identify trends and patterns

• Interpreting data to provide insights and recommendations to stakeholders

• Creating reports and presentations to communicate findings

• Ensur...read more
Answered by AI
Add your answer
Q3. What types of tools are used for data analysis?
Ans. 
Various tools such as Excel, Python, R, Tableau, and Power BI are commonly used for data analysis.
• Excel is commonly used for basic data analysis and visualization.

• Python and R are popular programming languages for statistical analysis and machine learning.

• Tableau and Power BI are used for creating interactive visualizations and dashboards.

• SQL is essential for querying databases and extracting relevant data.
Answered by AI
Add your answer
Q4. Is it a paid tool or does it offer a free demo?
Ans. 
The tool offers a free demo before purchasing the paid version.
• The tool offers a free demo for users to try out its features before committing to a paid subscription.

• The free demo may have limited functionality compared to the paid version.

• Users can upgrade to the paid version for access to additional features and support.

• Examples of tools that offer free demos include Tableau, IBM SPSS, and SEMrush.
Answered by AI
Add your answer
Q5. How much data do you extract on a daily or weekly basis?
Ans. 
I extract an average of 10,000 data points daily for analysis and reporting.
• On average, I extract around 10,000 data points daily for analysis.

• The amount of data extracted may vary depending on the project or research needs.

• I use various tools and software to efficiently extract and manage data.

• Examples of data sources include databases, APIs, web scraping, and surveys.
Answered by AI
Add your answer

Q1. Can you introduce yourself?
Ans. 
I am a data research executive with a background in statistics and experience in analyzing large datasets.
• Background in statistics

• Experience in analyzing large datasets

• Proficient in data research tools such as Python, R, and SQL
Answered by AI
Add your answer
Q2. How do you extract data from LinkedIn, and what tools do you use for this purpose?
Ans. 
I use web scraping tools like Octoparse or Import.io to extract data from LinkedIn.
• Use web scraping tools like Octoparse or Import.io to extract data from LinkedIn

• Identify the specific data you want to extract (e.g. job titles, company names, contact information)

• Set up the scraping tool to navigate through LinkedIn profiles and extract the desired data

• Export the extracted data into a usable format like CSV or Excel
Answered by AI
Add your answer
Q3. Are you comfortable with meeting targets in a target-based job?
Ans. 
Yes, I am comfortable with meeting targets in a target-based job.
• I have a proven track record of meeting and exceeding targets in my previous roles.

• I am highly motivated and thrive in a fast-paced, goal-oriented environment.

• I am skilled at setting realistic targets and developing strategies to achieve them.

• I am comfortable with the pressure that comes with working towards targets and see it as a challenge to overcome.
Answered by AI
Add your answer

They shortlisted my CV

Recruiter shared assignment with me

Q1. Meeting with Manager
Add your answer
Q2. Discussion about the role
Add your answer

Q1. Salary Discussion round
Add your answer