data scientist: the sexiest job in the 21st century

Presenter’s Name

Data Scientist: The Sexiest Job in the 21st Century

WUSS 2015

Experis | Monday, May 1, 2023 2

Our Time Today

– What is Data Science?– Who needs a Data Scientist?– What makes a Data Scientist?– What kind of Data Scientist are

you?

Specialized Talent and Solutions

New Work

Models

What is Data Science?

WUSS 2015


What is Data Science, anyway?

WUSS 2015


Hal Varian, the chief economist at Google, is known to have said, “The sexy job in the next 10 years will be statisticians. People think I’m joking, but who would’ve guessed that computer engineers would’ve been the sexy job of the 1990s?”

The Hot Job of the Decade

Source: HBR

WUSS 2015


The internet population now has over 2.1 billion people, and with every website browsed, status shared, and photo uploaded, we leave a digital trail that continually grows the hulking mass of big data.

Every minute, on average,

• YouTube users upload 48 hours of video• Facebook users share 684,478 pieces of content, • Instagram users share 3,600 new photos, and • Tumblr sees 27,778 new posts published.

A perspective on how Big is Data

Source: That Conference, 2015

WUSS 2015


“By 2015, 4.4 million IT jobs globally will be created to support big data, generating 1.9 million IT jobs in the United States,” said Peter Sondergaard, senior vice president at Gartner and global head of Research. “In addition, every big data-related role in the U.S. will create employment for three people outside of IT, so over the next four years a total of 6 million jobs in the U.S. will be generated by the information economy.“

Source:Gartner Symposium/ITxpo 2012

The Information Economy

Who needs a Data Scientist?

WUSS 2015

Experis | Monday, May 1, 2023 9Source- EMC

WUSS 2015


Chart via Forbes

http://www.forbes.com/sites/louiscolumbus/2014/12/29/where-big-data-jobs-will-be-in-2015/

WUSS 2015


Source: Data Science Central, 2015

Top Companies hiring Data Scientists

WUSS 2015


The Best Big Data And Business Analytics Companies To Work For In 2015

Source: Forbes

What makes a Data Scientist?

WUSS 2015


Source: Brendan Tierney - Oralytics Blog

http://www.oralytics.com/

http://www.oralytics.com/

WUSS 2015


Source: EMC

WUSS 2015


A big data scientist understands how to integrate multiple systems and data sets.

They need to be able to link and mash up distinctive data sets to discover new insights.

This often requires connecting different types of data sets in different forms as well as being able to work with potentially incomplete data sources and cleaning data sets to be able to use them.

Sound familiar?

WUSS 2015


8 Data Skills to Get You Hired

• Basic Tools• Basic Statistics • Machine Learning• Multivariable Calculus and Linear Algebra• Data Munging• Data Visualization & Communication• Software Engineering

Source: Udacity

WUSS 2015


Most in-demand data skills

Source: WANTED Analytics, 2014

http://blog.udacity.com/data-analyst-skills-checklist-eguide

Which Data Scientist are you?

WUSS 2015


Source: Udacity

4 Types of Data Science Roles

WUSS 2015


All joking aside, there are in fact some companies where being a data scientist is synonymous with being a data analyst.

Your job might consist of tasks like pulling data out of MySQL databases, becoming a master at Excel pivot tables, and producing basic data visualizations (e.g., line and bar charts).

You may on occasion analyze the results of an A/B test or take the lead on your company’s Google Analytics account.

.

A Data Scientist is a Data Analyst Who Lives in San Francisco:

WUSS 2015


You’ll see job postings listed under both “Data Scientist” and “Data Engineer” for this type of position.

Since you’d be (one of) the first data hires, there are likely many low-hanging fruit, making it less important that you’re a statistics or machine learning expert.

A data scientist with a software engineering background might excel at a company like this, where it’s more important that a data scientist make meaningful data-like contributions to the production code and provide basic insights and analyses.

Please Wrangle Our Data!

WUSS 2015


There are a number of companies for whom their data (or their data analysis platform) is their product. In this case, the data analysis or machine learning going on can be pretty intense.

This is probably the ideal situation for someone who has a formal mathematics, statistics, or physics background and is hoping to continue down a more academic path.

Data Scientists in this setting likely focus more on producing great data-driven products than they do answering operational questions for the company.

We Are Data. Data Is Us:

WUSS 2015


A lot of companies fall into this bucket. In this type of role, you’re joining an established team of other data scientists.

The company you’re interviewing for cares about data but probably isn’t a data company. It’s equally important that you can perform analysis, touch production code, visualize data, etc.

Generally, these companies are either looking for generalists or they’re looking to fill a specific niche where they feel their team is lacking, such as data visualization or machine learning.

Reasonably Sized Non-Data Companies Who Are Data-Driven:

WUSS 2015


Business Brain

• Concentrate on developing a “business brain” in addition to those hard data skills.

• Data insights are useless without the foundational knowledge of the business to which the data belongs.

• Keep your eyes and ears open to absorb as much understanding of how a business and strategy works.

• Develop presentations to advise senior management in clear language about the implications of their work for the organization.

• Develop ability to create examples, prototypes, demonstrations to help management better understand the work.

WUSS 2015


The Changing Role of Analysts

• Statistics done by non-Statisticians,• The growth of Statistics into new areas such as healthcare and financial

applications, • Greater expectations by management for statisticians to “be responsive

and vital to today's business needs and to be able to prove their contributions quantitatively,”

• The requirements of analyses to be timely as well as appropriate, • The need to work with immense databases, and • Adapting to new forms of communication. (Hahn & Hoerl, 1998)

Resources to Learn More

WUSS 2015


Resources for ongoing learning

WUSS 2015


As Peter Sondergaard, global head of research at Gartner, said in a 2012 statement,

The most valued data analysts of tomorrow will be able not only to derive insights from existing data sets, but also to tell the quantitative future:

“Dark data is the data being collected, but going unused despite its value. Leading organizations of the future will be distinguished by the quality of their predictive algorithms. This is the CIO challenge, and opportunity.”

In conclusion

http://www.gartner.com/newsroom/id/2207915

Presenter’s Name

Thank you

data scientist: the sexiest job in the 21st century

Data & Analytics