Data Analytics Internship
Thank you for showing interest in Business Quant’s data analytics internship program. If you’re reading this, then you’ve been shortlisted to work with us.
Please complete and submit the assignment shared below
Submission Deadline: 4pm on 30 October, 2022.
Aptitude test:
You may download this source file.
Then, use Python to:
- Identify last year’s sales for each item and save the values in a new column called “Sales Last Year”
- calculate sales growth for all the items and save the values in a new column titled “Sales Growth”. Formula shared below.
- Visualize the final table using any framework (Django or Flask) or python visualization library (example: dash, streamlit) of your choice.
- Have a filter on the “Items” column in the final visualization. This is very important.
Formula for Sales Growth % = (Sales in current year/Sales in Last year)-1
This is what your output should look like, with the user-selectable filters on “Items”
FAQs
No, this assignment is to assess your python skills. Please do it in python itself.
Django is our first preference.
You can also use Dash (by Plotly) or Streamlit.
But make sure to have the user-selectable filter on the
Sorry, this is a time-sensitive opening. We’ll be hiring on a first-come, first-serve basis (FIFO).
We’re not looking for charting capabilities in your aptitude test.
Requesting you to build your output as close to the dashboard shared above, with user-selectable filters on “Items” column.
2.1 GBs (bytes, not bits) and over 200 million rows of raw data. But that’s for later, when you begin your internship with us.
Some highlights of the internship program:
- Perform ETL using Python on over 20 million rows of data,
- Build and maintain web scrapers to build alternative datasets,
- Parse XML documents to build a proprietary database,
- Build a web app using Django.
Time commitment: 6-8 hours/day
Working days: Monday to Friday
Tenure: 3 months
Perks: Flexible work hours, letter of recommendation and experience letter.
How to Submit:
You may submit your solution at submissions@businessquant.com, containing:
- Full name
- The degree you’re currently pursuing
- Your college/university name
- The code itself
- A short video/gif of the output visualization
- Mention your system specs. Specifically:
- RAM in your notebook/PC (ex: 8GB, 4GB, 16GB)
- Processor (i3, i5, Ryzen with generation number ex: 10th gen i5)
If we like your submission, and its timeliness, we’ll schedule a phone interview with you to take your application forward.
I wish you all the best!
Regards,
Chetan
Data QA Analyst
Business Quant
