i
TVS Credit
Filter interviews by
I applied via Referral and was interviewed in Nov 2021. There was 1 interview round.
I am an experienced MIS Executive with a strong background in managing information systems and data analysis.
I have a Bachelor's degree in Management Information Systems.
I have worked for 5 years in a multinational company as an MIS Executive.
I am proficient in using various data analysis tools such as Excel, SQL, and Tableau.
I have successfully implemented automated reporting systems that improved efficiency and accur...
I applied via Walk-in and was interviewed before Dec 2020. There were 4 interview rounds.
I am an experienced analyst with a strong background in data analysis and problem-solving.
Experienced analyst with a track record of successfully analyzing complex data sets
Proficient in using various analytical tools and software
Strong problem-solving skills and ability to identify trends and patterns
Excellent communication and presentation skills
Ability to work well in a team and meet deadlines
Example: In my previous...
I applied via Referral and was interviewed before Jan 2024. There was 1 interview round.
I applied via Recruitment Consulltant and was interviewed before Nov 2023. There were 2 interview rounds.
Multiple Choice Questions
I applied via Walk-in and was interviewed in Apr 2024. There was 1 interview round.
An Excel file was given which had 2 sheets, sheet1 with raw data and sheet2 with task. There were 5-6 questions in Task. This tasks can be done by formulas such as CONCAT, Textjoin, Age calculation using Datedif, Vlookup, age band creation eg: 10-30,30-40 based on age I used nested IF, PIVOT Table
I applied via Walk-in and was interviewed in May 2022. There were 2 interview rounds.
Data frame making in Python involves creating a structured table-like data structure using the pandas library.
Use the pandas library to create a data frame
Data frames are 2-dimensional labeled data structures with columns of potentially different types
Data frames can be created from dictionaries, lists, numpy arrays, or other data frames
Example: df = pd.DataFrame({'A': [1, 2, 3], 'B': ['a', 'b', 'c']})
based on 4 reviews
Rating in categories
Assistant Manager
233
salaries
| ₹3 L/yr - ₹8.5 L/yr |
Field Officer
232
salaries
| ₹1 L/yr - ₹4.3 L/yr |
Collections Executive
223
salaries
| ₹0.8 L/yr - ₹4.5 L/yr |
Territory Sales Manager
221
salaries
| ₹3.5 L/yr - ₹8.4 L/yr |
Territory Manager
210
salaries
| ₹3 L/yr - ₹7.7 L/yr |
Muthoot Finance
IIFL Finance
Aavas Financiers
Muthoot Fincorp