The deck that I used during my talk at University of Engineering and Technology, Lahore about why and how to pivot from Electrical engineering to Data Science. Answers a number of critical questions like what is data science, how to become a data scientist and what are the career prospects in Data Science.

1. EE to DATA Science
Why and How of the Pivot
IRFAN ELAHI

2. About me?
About me
Currently:
Data Scientist in Deloitte Australia
Career Hops:
Network
Engineering
Start-up
(Network &
Systems)
Direct Selling
Start-up
(Retail/Web)
Digital Media
Data Science -
Academia

3. Data Science – The What?
What’s Happening
In companies out there?
What do Data Scientists
do?

4. Data Science – The Why?
Demand
Remuneration
Diversity
Purpose-Driven

5. Data Science – The Why?
Demand
Ranked First in 25 Best Jobs of 2016
Source: Glassdoor
“Why and How of the Pivot - IRFAN ELAHI

6. Data Science – The Why?
Demand
One of the toughest jobs to fill
Source: Forbes
Why and How of the Pivot - IRFAN ELAHI

7. Data Science – The Why?
Demand
Among 3 out of 10 Top Skills of 2016
Source: LinkedIn
Why and How of the Pivot - IRFAN ELAHI

8. Data Science – The Why?
Remuneration
Forecast to give highest pay hike in 2017
Source: SBS Australia
Data Science – The Why?
Remuneration
Why and How of the Pivot - IRFAN ELAHI

9. Why and How of the Pivot - IRFAN ELAHI

10. Data Science – The Why?
Remuneration
Data Scientist salaries are around 113% more than
average of all other jobs
Source: ReadWriteWeb
Data Science – The Why?
Remuneration
Why and How of the Pivot - IRFAN ELAHI

11. Data Science – The Why?
Remuneration
It’s Everywhere:
• Telco
• Health Care
• Financial Sector
• Energy Sector
• Retail
• Public Sector
• Web and others
Thus:
• More opportunities
• More alignment with your interests
Data Science – The Why?
Diversity
Why and How of the Pivot - IRFAN ELAHI

12. Data Science – The Why?
Remuneration
Data Science – The Why?
Diversity
Why and How of the Pivot - IRFAN ELAHI
DataScience
Machine Learning
Supervised
Regression
Classification
Unsupervised
Clustering
Dimensionality
Reduction
Feature Engineering
Semi Supervised
Learning
Probabilistic
Graphical Modelling
Distributed
Computing
Batch Hadoop
Streaming
Spark
Storm
Architectural
Framework
Deep Learning
Natural Language
Processing
Growing Ecosystem:

13. Data Science – The Why?
Remuneration
Data Science – The Why?
Purpose Driven
Why and How of the Pivot - IRFAN ELAHI
Data Science – The Why?
Purpose Driven
• Associates stronger meaning and
purpose in your career!
• Favours Objectivity
• Tangibly Improving Experience,
Efficiency and Productivity
• Disease Detection
• Crime Prediction
• Fraud Prevention
• Recommendation
• Cost Reduction
• Process Enhancement
• Massive sphere of impact

14. Data Science – The How?
Current Curricula’s Assessment
Bridging the gap
Data Science – The How?
Why and How of the Pivot - IRFAN ELAHI

15. Mathematics
& Statistics
Computer
Science
Domain Acumen and
Story Telling
Data
Science
What’s taught What’s missing
C Language Databases (SQL & No-SQL)
Data Structure Object Oriented
Programming
Operating Systems Functional Programming
Computer Networks Cloud/Distributed Computing
DevOps
Data Warehousing
What’s taught What’s missing
Calculus Advanced Statistics
Linear Algebra Data Mining
Stochastic Optimization
Differential
Equations
What’s taught What’s missing
Engineering
Economics
Presentation Skills
Communication
Skills
Effective Visualization
Stakeholder Engagement
• Good to know stuff:
• Network Security
• System Engineering and Administration
• User Experience
• Agile Principles
• Cloud Computing Providers (AWS, Azure)

16. • Self-Educate – Formal
Education simply isn’t enough!
• Coursera – Data Science Specialization
• Data Science Training A-Z (Udemy)
• edX – The Analytics Edge
• Udacity, InfiniteSkills
• SafariBooksOnline, PacktPublishing,
O’reilly
• Develop Soft-Skills
• Intellectual Curiosity
• Aptitude for Self-Education and Continued
Professional Development
• Cross-Functional Team Management Skills
• Develop compassion for effective story-
telling
Data Science – The How?
Bridging the Gap
Why and How of the Pivot - IRFAN ELAHI

17. Data Science – The How?
Bridging the Gap
• Build your personal brand
• Establish yourself as an authority
• Blog!
• Solve toy problems – Build stuff!
• Code in public
• Compete in competitions
• Participate in meetups
• Be active on LinkedIn
• Other tid-bits
• Be technology agnostic
• MSc and PhD really help but not mandatory
• Data Science skills applicable and valuable
in other domains
• Adhere to T Shaped Skills concept
• Get started with Python
Why and How of the Pivot - IRFAN ELAHI

18. Questions?