- [ ] R basics
- [ ] Packages : starguage ( to compare multiple packages)

Todo:
- [ ] New packages
- [ ] Pre processing steps
- [ ] joins

### rprop
categorical variable analysis

1. Job fit

ok

## Q. Why merkle ?

I was came to know about Merkle from my brother's friend Manaswi.

She shared with the that amazing work is being done at Merkle by amazing people and it is complemented by the achievements showcased on the companies website.

**talk about one example listed on website. answer is a bit short**

I am strong believer on teamwork and all the team members must be valued highly and these being in core values and beliefs at Merkle made me belive that i belong at merkle.

## Q. what are your career goals/interests?

I want to master the skills to provide helpful solutions to harness the power of data.

Challenge myself with handling big data diverse industries and teams, enjoy the journey and excel at what i do.
**become a technical expert in the field **

Down the line i would love to mentor the fresh ricruits and share my knowledge.

keeping updated with the latest technoligies and i am a voracious comic reader.

## Q. why are you fit for this role?

I am very detail oriented with strong customer obsession
and i will go above and beyond to provide
analytical solutions to our client.
I enjoy interacting with the client understading their pain points.
I enjoy working in different and challenging environments
i have a proven technical expertice to solve complex analytical problems and
providing solutions to our clients

**also i have am very eager to implement new skills and techniques that i have learnt in my masters and confident that i can bring value addition to solving problems for clients**

While preparing answer focus on
Unique value you bring to the team - like deep technical expertise, detail oriented and tell with examples

3. Track record of comparable results
Similar to achiever pattern - but find another example that is close to job description and explained the same way as achiever pattern

my first project when i was joined the team.
i tought of coming up with long term project.
were thinking

all the common reports.

We have developed the Tableau dashboard present few key metrics like:

I was tasked with providing solutions to the adhoc requests and we need to generate reports quarterly.
as it was done every quarted the task was not challenging enough so i have proposed to automate the processing steps. My manager was not convinced as it was beyond the scope of the project but i assured him that the assigned tasks would be completed and i want to take up this task along with it.

The test run ran very well my manager and the clients was very pleased by the interest shown by the team towards the task.

I have proposed to automated the preprocessing process for every quarter and process of

the client were surpriced and we were able to innovate on the tasks the client and the

small kt to the client.

4. One negative scenario:
where your project has difficulties in achieving/ran out of time.
Focus on why is it an obstacle,
why was it not identified in earlier stages.
How did you mange client.
what are the next steps taken to mitigate,
Lessons learned.

4. Technical/problem solving
q.. R related stuff.

5. Project review

# AMAZON

## Deliver Results
Q. Give me an example of a time when you were able to deliver an important project/ Achieved significant results/client was impressed/Challenging or tough project - similar type where interviewer is looking to gauge your achievements

While preparing answer write about below things
#### What was the goal? Why is this important?

**start that - there was a sitauation where our client was looking to understand churn rate**

The main goal of the project is to understand the customer churn and to come up with strategies to

#### What was your biggest contribution versus team? What unique value did you bring?

I have played a major part in identifying the data needed, performed EDA to gain uderstanding of the data, key variables and interactions among them and cleaning the data understanding the relationships/interactions among key variables, built a data pre processing pipeline(transformations in feature engineering)

THis played an important role as with the clean data building modelling part went smoothly.

I was able to provide my unique perspective of the data and was able to identify interesting relations among verious factors contributing to the customer churn.

The preprocessing pipeline was appreciated by my manager as only the model needs to be refreshed next time and has saved valuable project time.

#### What were the most significant obstacles you faced? How did you overcome them?

Messy data and Understanding it was trouble some the begining.
I was able to over come it by focusing on different sections. documenting my understanding and enjoying the small steps completition.

The new members in the team facing the same issue i have proposed the same strategy which worked for me. by reping the sucess of small steps help the team mate to become more interested in the work and i was very happy with the outcome.

tackling challenging work gives is one of the favorate part.
That has turned into a very big road block for us

#### How did you measure success for this project? What results did you achieve?$Cost savings, revenue generation# Quantify to understand volume, size, scale

Initial success was measured with accuracy of the model on the test data.
We proposed three approaches to improve the retention of our existing customers.
Strategy deployement channels: Call email and direct mail

measured the success on the rate of improvement on renewals from previous month and and the role of the targeted customers.

This was repeated for the three months and measured the rate of success for alll the channels.

feedback was taken from it and we have changed the channel width accordingly.

checked the the rate policy renewals in 1 month and it was an improvement of 10 percent from previous month. and have verified the target customers played key role

###prepare scenarious for these

## customer obsession
### type of questions:
difficult interaction, abive and beyond

## ownership
where you didnt meet a commitment
task out of primary responsibility

## Learn and Curious
### type of questions:
indepth knowledge to solve something case

out of comfort zone work

didnt know what to do next

## Invent and Simplify
### type of questions:
simple solutiin to hard problem , innivative thing

diff between transactional and data warehouse datavase

d b/w er modeling and dimension modeling

normal forms ? bcnf

advantages of star schema design

different types of slow changing dimensions SCD (type 1 2 3) and their differences

difference between DE and OLTP systems

full/initial load and incremental/refresh load

staging area

data mart

star and snow flake schema difference

investigate abd tune a poorly performing report/etl process

10 billion records . how do u add a new column and back fill the data from source withiut impactinf users

best way to delete 100 million from 1 billion table