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I applied via Referral and was interviewed before Jun 2023. There were 3 interview rounds.
2 DSA, 1 SQL, 5 ML MCQ
I applied via LinkedIn and was interviewed in Jan 2024. There were 3 interview rounds.
There was an online aptitude test duration of 30 mins and topics covered (maths,stats,tech)
Hacathon test with java and python
I am responsible for assisting in various tasks and projects within the company.
Supporting team members in daily operations
Completing assigned tasks in a timely manner
Assisting in research and analysis
Participating in meetings and discussions
CTC stands for Cost to Company, which includes all expenses related to an employee's compensation.
CTC includes salary, bonuses, benefits, and any other perks provided by the company
It is the total amount of money a company spends on an employee in a year
CTC is often used to negotiate job offers and understand the full value of a compensation package
I applied via Campus Placement and was interviewed before Nov 2023. There were 2 interview rounds.
Basic python, sql and pandas questions
posted on 29 Mar 2024
I applied via Referral and was interviewed before Mar 2023. There were 2 interview rounds.
Intermediate level coding round
Developed a predictive analytics model to forecast customer churn for a telecommunications company.
Collected and cleaned customer data from various sources
Performed exploratory data analysis to identify patterns and trends
Built a machine learning model using logistic regression to predict customer churn
Evaluated the model's performance using metrics such as accuracy, precision, and recall
I applied via Referral and was interviewed in Sep 2023. There were 4 interview rounds.
Technical SQL Coding Round of 1 hour
Began with 2 easy generic question -
1. No. of record on different types of joins.
2. Employees who have higher salaries than their managers,
Then moved to medium questions -
1. Implement Rolling sum with & without window functions.
2. Other questions were on CTEs, Joins & other complex queries.
Bar Raiser Round of 1 hour involving -
1. Case study: How can we leverage product knowledge & analytics to increase Amazon Prime Revenue from 10% to 12%?
2. Metrics awareness: Common metrics discussion like DAU, PDAU, MAU, Retention, Churn, etc.
3. Resume based work exp discussion
I appeared for an interview in Dec 2021.
Round duration - 90 Minutes
Round difficulty - Easy
Problem solving using SQL questions
Round duration - 90 Minutes
Round difficulty - Easy
A marketing campaign is run, how will you decide metrics to be tracked. Techincaly a KPI round
Metrics selection based on campaign objectives, target audience, and key performance indicators.
Identify campaign objectives and goals
Consider target audience and their behavior
Select key performance indicators (KPIs) relevant to the campaign
Track metrics such as conversion rate, click-through rate, ROI, customer acquisition cost
Analyze data to measure success and make data-driven decisions
Round duration - 30 Minutes
Round difficulty - Easy
Social empathatic fit round
Tip 1 : SQL logics to be understood completely
Tip 2 : A good running working logic of Python
Tip 3 : Basics of Dashboarding
Tip 1 : One pager , single column resume which shows all your skills
Tip 2 : Mention all things that make you relevant for the job
I applied via Referral and was interviewed before May 2023. There was 1 interview round.
Window functions are used in SQL to perform calculations across a set of table rows related to the current row.
Types include ROW_NUMBER(), RANK(), DENSE_RANK(), NTILE(), LAG(), LEAD(), FIRST_VALUE(), LAST_VALUE(), etc.
They allow for calculations to be performed on a specific subset of rows within a query result set.
Window functions are commonly used for running totals, moving averages, and ranking data.
Joins are used to combine rows from two or more tables based on a related column between them.
Inner Join: Returns rows when there is a match in both tables.
Left Join: Returns all rows from the left table and the matched rows from the right table.
Right Join: Returns all rows from the right table and the matched rows from the left table.
Full Outer Join: Returns rows when there is a match in one of the tables.
Cross Join:
based on 1 interview
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