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MagicPin Key Relationship Manager Interview Questions and Answers for Experienced
MagicPin Key Relationship Manager Interview Experiences for Experienced
1 interview found
Anonymous
I applied via LinkedIn and was interviewed before Sep 2021. There was 1 interview round.
(5 Questions)
- Q1. Siple basic questions like how are you doing and all and how many holidays u can take
- Q2. Dont ask for holidays
- Q3. U cannot get sick and cannot ask for any leave
- Q4. Target have to complete else you are not allowed to go back home .
- Q5. Have to report on time but going home is not fix
Interview Preparation Tips
- General knowledge
Interview questions from similar companies
Selected
I applied via LinkedIn and was interviewed in Aug 2022. There were 3 interview rounds.
(2 Questions)
- Q1. Questions related to SCM
- Q2. Bucket level creation
(2 Questions)
- Q1. Reports and tracking required.
- Q2. How to deal with low fill rate
- Ans.
Low fill rate can be dealt with by analyzing the root cause and implementing corrective actions.
Analyze the reasons for low fill rate such as inaccurate forecasting, poor inventory management, or supplier issues
Implement corrective actions such as improving forecasting accuracy, optimizing inventory levels, or finding alternative suppliers
Regularly monitor and measure fill rate to ensure improvements are sustained
Colla...
Interview Preparation Tips
Prepare your function well.
(2 Questions)
- Q1. What do you think we do at Impact Guru
- Q2. Give a brief introduction about yourself
Interview Preparation Tips
HR team is best
Join the team
amit badave
(1 Question)
- Q1. Last organisation experiance
Interview Questionnaire
2 Questions
- Q1. SQL and Excel were the key that helped me get this job.
- Q2. Puzzles
I applied via Walk-in and was interviewed before Feb 2021. There were 3 interview rounds.
(1 Question)
- Q1. Tell me about yourself.
Interview Preparation Tips
I applied via Campus Placement and was interviewed in Dec 2021. There were 4 interview rounds.
Interview Questionnaire
1 Question
- Q1. Sell the bottle
- Ans.
Our bottle is the perfect combination of style and functionality, making it the ideal choice for anyone on the go.
Our bottle is made from high-quality, durable materials that will last for years to come.
It features a sleek, modern design that is sure to turn heads wherever you go.
The bottle is also incredibly easy to use, with a simple twist-off cap that makes it easy to fill and clean.
Whether you're heading to the gym...
Interview Preparation Tips
I applied via Company Website and was interviewed in Sep 2022. There was 1 interview round.
(2 Questions)
- Q1. How is this company running?
- Q2. It is helpful for students
Interview Preparation Tips
- Data Entry
I applied via LinkedIn and was interviewed in May 2023. There were 3 interview rounds.
Send assignment doings MS Excel
(2 Questions)
- Q1. Asked about the previous project
- Q2. What about your roles in previous company
Interview Preparation Tips
- Excel
Shubham Upadhyay
(3 Questions)
- Q1. 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 unique ranks to each distinct value in a dataset
Dense rank does not leave gaps between ranks, assigning consecutive ranks to values with the same rank
For example, if values are 10, 20, 20, 30, then rank would be 1, 2, 2, 4 and dense rank would be 1, 2, 2, 3
- Q2. How will merge multiple file in python
- Ans.
Merge multiple files in Python using pandas.concat() or pd.merge() functions.
Use pandas.concat() function to merge multiple files vertically (row-wise).
Use pd.merge() function to merge multiple files horizontally (column-wise) based on a common column.
Ensure that the files have compatible column names and data types before merging.
Handle any missing or duplicate values appropriately during the merging process.
Consider ...
- Q3. Data frame explain in detail
- Ans.
A data frame is a two-dimensional data structure in which data is stored in rows and columns.
Data frames are commonly used in programming languages like R and Python for data analysis.
Each column in a data frame represents a variable, while each row represents an observation.
Data frames can contain different types of data, such as numeric, character, and factor.
Data frames can be created from various sources like CSV f
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