Final presentation for Brilent bootcamp

1. Analytical Jobs
Demand Analysis
Jason Zhang/Bilong Chen
Final Presentation

2. Objective
Understand the demand of analytics jobs
a. What is the trend of demands for analyst?
b. Which location/industry the demand come from?
c. What degree is required to launch job in analytics?
d. What skills are needed in the analytics jobs?

3. Approach
Data
Source
Extracted
Features
● Job Title
● Company Name
● Company Type
● Company Industry
● Job Location
● Key Skills (SQL,
Python, etc)
● Degree
Web
Scrape
Database
Text
Mining CouchDB
NoSQL DB
Second Hand Data
First Hand Data
Indeed
Trend Search

4. Definition
What do we mean by “analyst”?
Analyst
Data Analyst
(Engineer)
Business Analyst
(Business)
Match Keywords
data engineer, data scientist, machine
learning, technical analyst, system analyst,
security analyst, data modeler, data
architect etc.
Match Keywords
business intelligence,
business analyst, program manager,
product manager, marketing,
and other analysts not categorized as
data analyst (engineer)
who is responsible for
designing algorithms, softwares, or
infrastructure that enable analysis
who is responsible for
conducting decision-related analysis
and communicate w/ client

5. Business Analyst (Business) is four time
as much as Data Analyst (Engineer)
4,000+
16,000+
* Number of Active Job Posts on Linkedin Given the Pre-selected Keywords

6. What is the trend of
demands for analyst?

7. “Analyst“ position shifts title over time
Data Scientist
Data Analyst Business Analyst
Business Intelligence

8. Big Data Related Job Increased Steadily
NoSQL Hadoop
Big Data

9. What is the source
(location/industry) of the demands?

10. Most western opportunities are located at CA while
eastern opportunities are even distributed

11. Business Analyst is more evenly distributed
across four regions

12. Demand for Business Analyst and Data Analyst
are slightly different across industries
Top1
for Both Role
* which industry the job belong comes from the Linkedin company profile page

13. What is the degree requirement
for the analyst position

14. Data Analyst (Engineer) has higher preference towards
Ph.D than Business Analyst (Business)
65% jobs express
degree requirement
65%
% of Job Mentioning BS/MS/Phd
18%
PhD
Only

15. What skills companies want
from their analysts?

16. Data Analyst has more specific
skills requirement than Business Analyst
Data Analyst
(Engineer Side)
Business Analyst
(Business Side)
3.0 1.3
# of Skills Required in the Job Post
* Among the extracted skill set, on average,
data analyst position requires 3.0 skills while business requires 1.3 skills

17. SQL is the most important skill for Analyst (Engineer)
as Excel for Analyst (Business).
SQL
High for Engineer
Excel
High for Business
Java, Hadoop, Python
R, SAS, Machine Learning
Moderate for Engineer
Presentation
Moderate for Business

18. What is the trend of the demand
for those high/moderate skills?
Python R Machine L’ning
Hadoop SAS Java
Excel Presentation SQL

19. What about the trend for the skill
Business Engineer
High Moderate High Moderate
Excel Presentation SQL Python, R, ML, Hadoop SAS, Java

20. Takeaway
For Staffing and Recruiting Company:
1. Monitor skills instead of job titles
2. Focus on “Business Analysis” if the company want to
expand business in eastern coast
3. Help candidates prepare interview by helping them
enhance top required skills (SQL, Presentation)

21. Q & A
Thanks you!

22. Appendix

23. Top 1 State - California vs. Top 1 City - New York
Top 5 States Top 5 Cities

24. Analysis Tend

25. The skill requirement of analyst is very diverse -
not a skills satisfy more than half of the jobs
Top 20 Skills for Analytical Positions
NO skill can satisfy
the requirement of
more than 35% jobs

26. Limitations/Next Steps
Limitations
1. Single Source: Job data is only from single source (only Linkedin)
2. Only June/July data could be crawled, no time series analysis could
be done with our own data
3. No way to detect job duplication (single job, multiple posts)
Next Step
1. Scrape data from multiple sources (indeed, monster)
2. Run the script weekly so calculate job data over time
3. Calculate the similar of two job posts to reduce duplication
4. Store the job into MySQL database

27. Appendix

28. Appendix

29. Appendix