The impact of data science on business is undeniable, and the value it provides is growing without signs of slowing. To keep up with this rapidly evolving technology landscape, data scientists must adapt and specialize through continuous learning. This talk focuses on how they can do that in a way that maximizes the positive impact data science will have on their organization.

1. The Evolving Data Science Landscape
Kyle Polich
Data Science, Inc.

2. LIGO
One of the most
advanced metrology
projects; one of the
more precise
instruments ever
created
2
Measures changes
1 / 10,000th the
width of a proton
4km interferometer
to measure
gravitational
fluctuations from
cosmic explosions

3. LIGO
According to Scientific American, cost $1.1 billion over last 40 years
3
Turned on in 2002Construction took
8 years
Managed by ~1k
scientists
Gravity waves
detected 2016

4. Value Delivery
“Despite the hype of big data, a majority of the business value
produced by data still happens in this more traditional setting, and
we would like to support these communities.”
- Szilard Pafka (Dec, 2014) announcing new
- DW/BI/Analytics Meetup
4

5. Bias, Variance, Heterogeneity
“Up until late last year, tracking would be done unpredictably after
almost every release.”
“We changed the way we capture that last April and again this
January.”
“We have four divisions that all do their analytics differently.”
5

6. Excitement Scale
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7. Excitement hierarchy
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Report generation
ML on 10k observations, 20 features
ML on 1 billion observations, 1500 features
ML on 1 million observations, 100 features
1000 node clustered computing
A/B testing
High performance computing
Econometric modeling for adtech
Deep
learning
SQL queriesLogistic regression
Off the shelf OpenCV implementation
Online multi-armed bandit
Online streaming algorithms
Commercial opportunities for quantum computing

8. Measures of effectiveness?
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F1-scoreAccuracy and
precision
Area under an ROC
curve (AUC)
Bias-variance
tradeoff

9. Measure of effectiveness
 Return on Investment (ROI)
 Revenue savings from automation
 Lift
 Impact Factor*
 Causal Impact
 Value of information
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10. Goodhart’s Law
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When a measure becomes a target, it ceases to be a good measure

11. Value of Information
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Expected Revenue
if information know=Value
(information)
Expected revenue if
Information NOT
know- - Cost of
Information

12. Iteration and precision
Early objectives
• Maximize conversion rate
• Send / don’t send offer
• Raise / lower budget
• Predict number of machine failures
• Find available service provider
Late objectives
• Maximize lifetime value
• Personalized offer
• Real time bid optimization
• Optimize factory environmental
controls
• Global service pairing optimization
12

13. Business Conversations
Optimize within the constraints of your product
Discuss opportunities with product owner
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14. The Evolution of Software Engineering
Angular developer, UI/UX architect, AWS Infrastructure engineer, Spring
integration manager, DevOps engineer, Change management / continuous
integration specialist, Security engineer, Unity developer, Serverless
evangelist, mobile developer, wordpress developer, Accessibility specialist
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Pre
1990s
1990s
2000s
DBA, VLSI engineer, Embedded systems
programmer, Front end, back end, QA
“Computer Programmer”

15. Scope of Data Science
15
Pre
2008
2008-
2016
2016-

Statistician, ML researcher, etc.
Data scientist, data engineer
2016 – Future ???

16. An arbitrary timeline
1950s
1993
1993
1995
2001
2004
2007
2010
2011
2014
2015
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Perceptron algorithm
R first appearance
C4.5 described
False discovery rates
Weka
MapReduce paper
Scikit learn initial release
Theano
h2o launched
Spark initial release, XGBoost on github
Tensorflow

17. 17

18. Data science community
 Meetups
 Events
 MOOCs
 Bootcamps
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 Podcasts
 Blogs
 Books

19. DataForward Event Series
DataForward is a gathering of professionals across industries who are passionate about data
science, big data technologies, and data driven businesses. The group meets once a month at
keynote events featuring talks and presentations by industry leaders. The DataForward events
are hosted and organized by DataScience Inc, and livestreamed to audiences all over the
world.
The monthly events are dedicated to key topics facing data-driven organizations- disruptive
technologies, data-driven culture, investment trends, and insights into how existing
organizations can unlock the value from their data. To signup for our first keynote event in
August, please visit meetup.com/DataForward.
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20. DataScience
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facebook.com/datascience
twitter.com/datascienceinc
linkedin.com/company/datascience-inc
(310) 579 - 6200