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I applied via Naukri.com and was interviewed in Dec 2024. There was 1 interview round.
Developed a predictive model to forecast customer churn for a telecom company.
Collected and cleaned customer data including usage patterns and demographics.
Used machine learning algorithms such as logistic regression and random forest to build the model.
Evaluated the model's performance using metrics like accuracy, precision, and recall.
Provided actionable insights to the company based on the model's predictions.
Data Analyst focuses on analyzing data to provide insights, while Data Scientist focuses on using advanced algorithms and machine learning to predict future trends.
Data Analyst focuses on analyzing data to provide insights for decision-making.
Data Scientist focuses on using advanced algorithms and machine learning to predict future trends.
Data Analyst typically works with structured data, while Data Scientist works wit...
I applied via Referral and was interviewed in Jun 2023. There were 2 interview rounds.
I applied via Referral and was interviewed in Nov 2024. There were 2 interview rounds.
I applied via Job Portal
I applied via LinkedIn and was interviewed in Dec 2022. There were 3 interview rounds.
Contains math aptitide and basic tableau questions
Sql coding test with joins sub queries and stored procedures
I applied via Campus Placement and was interviewed in Sep 2023. There was 1 interview round.
KPI's for the ecommerce industries
posted on 26 Jan 2025
I appeared for an interview before Jan 2024.
I applied via Naukri.com and was interviewed in Nov 2020. There was 1 interview round.
Statistics is the study of collecting, analyzing, and interpreting data.
Descriptive statistics summarize and describe data
Inferential statistics make predictions and draw conclusions about a population based on a sample
Hypothesis testing is used to determine if there is a significant difference between groups
Regression analysis is used to model the relationship between variables
Probability theory is used to quantify un...
Rank assigns unique ranks to each distinct value, while dense rank does not leave gaps between ranks.
Rank assigns consecutive integers to each distinct value based on their order.
Dense rank also assigns consecutive integers, but does not leave gaps between ranks.
For example, if we have values 10, 20, 20, 30, then rank would be 1, 2, 2, 4 and dense rank would be 1, 2, 2, 3.
RLS in Power Bi stands for Row-Level Security, which allows users to restrict access to data based on their role or profile.
RLS in Power Bi is used to control access to data at the row level
It allows users to define rules to restrict data based on their role or profile
RLS can be implemented using DAX expressions to filter data dynamically
For example, a sales manager can only see data related to their region using RLS
Identifying time for a project involves creating a timeline, setting deadlines, and monitoring progress.
Create a project timeline outlining key milestones and tasks
Set deadlines for each task to ensure timely completion
Monitor progress regularly to identify any delays and adjust timelines accordingly
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