The most valued data science skills!

Team 3
03/30/2017

Introduction

As part of the course curriculum:

  • This project exposes the entire team to a broad array of skills including communications, team building, goal setting, task identification and delegation.

  • In a nutshell, this project can be summarized as building project management skills with virtual teams.

Team 3

CUNY MSDA

DATA 607

Name Team Email
Pavan Akula Team 3 akulapavan@hotmail.com
Ambra Baboni Alexander Team 3 ambra8due@hotmail.com
Thomas Detzel Team 3 tomdetz@gmail.com
Dilip Ganesan Team 3 dilipgan@gmail.com
Kyle Gilde Team 3 kylegilde@gmail.com
Raghunathan Rammnath Team 3 raghu74us@gmail.com
Duubar Villalobos Jimenez Team 3 mydvtech@gmail.com

Overview

We have gathered our data from:

https://www.paysa.com/

“Get paid what you deserve!”

Project - Data Science Skills

Sample of job listings for “Data Science”.

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“Data Science” postings with desired listed skills.

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Sample of our Paysa.txt file.

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Tidy table

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Top 10 most desired skills by Employers.

Project - Data Science Skills

Top 10 most desired skills by Employers.

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The MOST desired skill by employers

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Top 10 offered salaries

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Top 10 signing bonus

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Top 10 annual bonus

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Top 10 base salaries

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Top ranked skills vs highest paid

The top 6 skills, represent the best combination for highest salary!

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Highest-Valued Skills Measured by Mean Compensation

  • Some of the highest-valued skills are not the most common skills. They include Strategy, Leadership, Management and Data Science, a catch-all. ETL - for Extract, Transfer and Load - is a critical area of data warehousing.

Project - Data Science Skills

Highest-Valued Skills Measured by Mean Compensation

  • This part of the analysis looks at the value of skills based on what employers pay rather the frequency of skills in a job posting. To do this, we compute a mean value for each skill across the database.

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Highest-Valued Skills Measured by Mean Compensation

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Relative Value of Skills

Using ANOVA

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Salary weight composition

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Big Challenges

  • Trust was observed as a critical factor for effective communication in the team.

  • Having a clear vision for the team.

  • Creating team spirit and team goals.

  • Prioritizing the tasks.

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Communications Management

  • Face-to-face communication was beneficial.

  • Logging what, who and how and frequency.

  • Logging origination, nuances.

  • Recognizing team members accomplishments.

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Communication Tools

  • Slack and What's App: Social media tool, to communicate with team members.

  • Join Me: For voice calls and idea presentation.

  • Github: Code sharing.

  • R Studio: Primary development tool.

  • MySQL: RDBMS used to store data in normalized format.

  • Google Spreadsheets: Monitoring and managing tasks.

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Output

  • Remotely, comparable to what we would have got working locally.

  • Our team was smart.

  • Could think for themselves.

  • Innovative and well educated in their tasks.

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Conclusions

  • Project: Management Skills

  • Virtual Teams versus Face-to-Face Teams.

  • Working with geographically distributed professionals.

  • Collaborate on a variety of workplace tasks.

  • Effectiveness of information exchange.

  • Creating trust and Keeping motivated.

Team

  • Duubar Villalobos: Team leader, coordinating entire team from task identification to delegation.
  • Tom Detzel: Dataset Analyst, major in role in identifying the dataset. Web Scrapping and harvesting raw data.
  • Pavan Akula: Data modeler, MySQL database design.
  • Kyle Glide: Data wrangler, Tidying and Formatting data to store data into MySQL DB.
  • Ambra Barboni-Alexander: Data wrangler, Tidying and Formatting data to store data into MySQL DB.
  • Raghunathan Ramnath: Data wrangler, Tidying and Formatting data to store data into MySQL DB.
  • Dilip Ganesan: Data wrangler, Pattern recognition and producing raw dataset.

Project - Data Science Skills