Ann Rajaram
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Short Bio:
#DataScience & #ArtificialIntelligence professional, working on credit card fraud #Analytics at TDBank. Love books, travel and blogging.
Published author of book - "Data Scienc Jobs", available on Amazon - https://amzn.to/2X31Fav
Follow me on Twitter at @anu_analytics.
Job Title:
Analytics Manager
Job Function:
Data Science, Machine Learning, AI, Business Analytics
Banking & Finance
LinkedIn Profile:
Contributing, Networking, Finding a new position, New venture

Ann Rajaram's Blog

How do I prepare for Data Scientist interviews?

Posted on July 11, 2019 at 2:52pm 0 Comments

If you are a recent graduate or someone preparing for your first data scientist position, then here are some tips to help you ace your interview!…


Data Science Jobs - eBook Summary

Posted on May 25, 2019 at 12:00pm 0 Comments

As a senior datascience professional and analytics manager, I get countless requests for job search advice, resume feedback and heart-breaking stories from brilliant students who are unable to snag a job in this exciting field. There are tons of books on how to learn the skills to become a data scientist/ data analyst, but none to prepare folks for the frustrating job search.

I've repeated this advice to dozens of people, most of whom found their dream datascience job with…


Who are the Datascience Professionals? India vs US | Men vs Women

Posted on November 6, 2018 at 2:39am 1 Comment


This is an analysis of the Kaggle 2018 survey dataset. In my analysis I am trying to understand the similarities and differences between men and women users from US and India, since these are the two biggest segments of the respondent population. The number of respondents who chose something other than Male/Female is quite low, so I excluded that subset as well.

The complete code is available as a …


Who will get hired at Google?

Posted on January 15, 2018 at 5:30pm 2 Comments

In this script, we will explore the open roles at Google, and try to see what common attributes Google is looking for, in future employees. 

This dataset contains text information about job location, title, department, minimum and preferred qualifications and the responsibilities of the position. Using this dataset we will try to answer the following questions:

  1. Where are the open roles?
  2. What are the minimum and preferred educational qualifications needed…

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