Roberto Muñoz is an astronomer and data scientist with a PhD in astronomy and extensive experience in academia, transitioning to industry as a research officer at MetricArts. His work includes significant surveys of galaxy clusters, collaboration between academia and industry, and involvement in various data-intensive projects. The document highlights challenges in science funding and the evolving landscape of data science, emphasizing the need for interdisciplinary skills and practical experience for career advancement.

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Roberto Muñoz
Astronomer & Data Scientist
Research Officer at MetricArts
@RobertoKPax

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My
Journey
M y J o u r n e y i n
A c a d e m i a

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2 0 0 9
PhD degree in Astronomy
Ponticifia Universidad Católica de Chile
2 0 1 2 - 2 0 1 5
Postdoctoral researcher
Pontificia Universidad Católica de Chile
2 0 1 0 - 2 0 1 1
Postdoctoral researcher
Strasbourg University, France
THROUGH THE TIME
Worked in Academia for about 6 years

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The Next Generation Virgo survey (NGVS) is
a wide, deep and panchromatic survey of
the Virgo cluster. Area 100 deg2.
Combining optical and near-infrared bands
I found a clear separation between Galactic
sources, extragalactic GCs and galaxies.
Virgo cluster and
uiK diagram
A h i d d e n t r e a s u r e
M u ñ o z e t a l . 2 0 1 4

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The Next Fornax Survey (NGFS) is a
panchromatic survey of the Fornax
cluster.
Study giant and dwarf galaxies, GCs and
UCDs.
Fornax cluster and
dwarf galaxies
H u n t i n g g h o s t s
M u ñ o z e t a l . 2 0 1 5

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Full of dwarfs
643 dwarf galaxies in Fornax
One of the largest catalog of dwarf
galaxies belonging to a structure
Ó r d e n e s - B r i c e ñ o e t a l . 2 0 1 8

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Science funding
crisis
Public budget cuts, Excessive
bureaucracy, Poorly defined
research policies

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Science by
the numbers
S c i e n c e b y
t h e n u m b e r s

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Number of researchers
Number of researchers per 1,000 workers
9.1 scientists per
1K workers
USA
10.1 scientists
per 1K workers
France
9 scientists per
1K workers
Germany
USA
France
Germany

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Number of researchers
Number of researchers per 1,000 workers
1 scientist per
1K workers
Chile
2.9 scientists
per 1K workers
Argentina
0.7 scientists
per 1K workers
Brazil
Chile
Argentina
Brazil

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R&D funding
Gross domestic spending on R&D
2.7% of GPD
USA
2.3% of GDP
France
2.7% of GDP
Germany
USA
France
Germany

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R&D funding
Gross domestic spending on R&D
0.38% of GDP
Chile
0.63% of GDP
Argentina
1.2% of GDP
Brazil
Chile
Argentina
Brazil

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What about Chile?
The National Association of Researchers
of Chile (ANIP) conducted a survey
about working conditions.
79%
9%
5%
Working in Universities
Working in Research centers
Working in Industry

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Chile vs Germany
Employed doctorate holders by economic sector
65%5% Startups, Companies
I n d u s t r y
19%79% Public and Private
Universities, Professional
institutes
A c a d e m i a

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First
approach
F i r s t a p p r o a c h
t o I n d u s t r y

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2 0 1 6
Collaboration Academia-Industry
Ministry of Economy funding
2 0 1 5
Invited by a company to
collaborate
TO D A Y
Data scientist and Research Officer
Chilean company MetricArts
THROUGH THE TIME
Decided to move to Industry

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The company was looking for new
business opportunities and wanted to
explore data intensive solutions.
Meet the company
MetricArts is a Chilean company funded in
2007. It started as a Business Intelligence
company and nowadays is a technology
solutions company.

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Collaboration
2 0 1 5
The company wanted to explore the new
services of the platform Microsoft Azure.
Several clients were interested in buying
new services, such as image and text
analysis.
Cloud computing, Cognitive analytics.

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University-Industry
2 0 1 6
We got funding from the Ministry of
Economy for running a project between
the Institute of Astrophysics at PUC
and the company MetricArts.
Still working at the University.
Develop a computer vision system for
processing surveillance cameras.

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Industrial R&D
T o d a y
On 2017 I decided to leave the
academic career and joined a company.
The R&D team at MetricArts consists of
3 scientists and 5 engineers.
• Computer Vision
• Machine Learning
• Data Intensive Analytics
• Cloud computing

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Industrial R&D
T o d a y
Daily activities
• Read papers
• Code new algorithms
• Train machine learning models
• Develop prototypes
• Meet with sales team and evaluate
technical challenges
• Meet with engineering and BI teams
• Improve deployed systems
• Submit papers and attend
conferences

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Data Science
and IT industry
D a t a S c i e n c e
a n d I T i n d u s t r y

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S t or e
Databases, Excel,
XML, JSON
R e t r i e v e
SQL, Data Lake,, Data
Warehouse
Tr a ns m i t
Transmission,
Propagation,
Reception
M a ni pu l a t e
Data Analysis, Data
mining
Information
Technology
Application of computers to Store,
Retrieve, Transmit and Manipulate Data

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E m p l o y m e n t o f c o m p u t e r
a n d i n f o r m a t i o n t e c h n o l o g y
o c c u p a t i o n s i s p r o j e c t e d t o
g r o w 1 3 % f r o m 2 0 1 6 t o 2 0 2 6 .
* B u r e a u o f L a b o r S t a t i s t i c s , U S A
Job market
C o m p u t e r a n d I n f o r m a t i o n
s y s t e m s a r e e s s e n t i a l p a r t s
o f e v e r y b u s i n e s s t o d a y .
F i n a n c e a n d h e a l t h c a r e
a r e t h e b e s t c l i e n t s .
Business

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A new paradigm
Jim Gray, researcher of Microsoft
talked about the Fourth paradigm
The digital era and new technologies have
changed our life style..
The first three paradigms were experimental,
theoretical and, more recently,
computational science.
We are living in the data-driven era.

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Data Science
Interdisciplinary field that applies and
develops new methods to extract
information from data.
Pr og r a m m i n g S t a t i s t i c s
M a c hi ne L e a r ni ng D om a i n

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T h e D a t a S c i e n c e V e n n D i a g r a m
D r e w C o n w a y ( 2 0 1 0 )
Programming
Exploratory analysis
Analytical thinking
Modeling
Domain knowledge
Business experience

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T - s h a p e d v s P i - s h a p e d
A l e x S z a l a y
New breed
Classic PhD program generates T-shaped researchers:
scientists with wide-but-shallow general knowledge, but deep
skill and expertise in one particular area.
New breed of scientific researchers must be Pi-shaped:
maintain the same wide breadth, but push deeper both in their
own subject area and in statistics/computational methods.

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Data is growing exponentially and
standard methods and tools are not
enough.
Facebook and Google ingest more than
500 TB of data per day.
Big Data
N e w m e t h o d s a n d t o o l s

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Few companies have to deal with Terabytes
and Petabytes datasets.
Companies generate and accumulate lot of
unstructured data. Variety is a challenge.
Sensors are common nowadays and IoT
industry is growing fast. Processing real-time
data is a challenge.
The three Vs
N o t j u s t V o l u m e

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Cross-Infrastructure/Analytics
S h o u l d e r o f g i a n t s

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Advices
A d v i c e s

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There are multiple online courses about
Data Analysis, Data Science,
Visualization, Machine Learning,.
Take online
courses
K n o w l e d g e a n d C e r t i f i c at e s

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Python and R are the most used
languages in data analysis. More than 40
million users.
SQL is from 70’s but still very used by
many companies.
Learn modern
languages
D a t a - s c i e nc e l a n g u a g e s

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You can start from an already existing
projects and make small changes.
Look for public datasets and try new
ways to analyze and visualize data. Ask
the right questions.
Do independent
projects
T r y n e w i d e a s

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Github is a code hosting platform for version
control and collaboration. It allows to create
private and public code repositories.
Start with simple projects and then move to
more complex projects in Github.
Open a Github
account
S h o w y o u r c o d e s

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Internships offer students a period of
practical experience in the industry.
Unlike conventional employment,
internships have an emphasis on training.
Do internships
L a n d i n a c o m p a n y

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Write a short story about your background
and projects you have been involved
List the software, tools and programming
languages you have experience.
Make emphasis in your soft and technical
skills related to the job you are applying.
Improve your CV
In the industry, the main purpose of a
CV is to get job interviews.

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Upload your CV in Linkedin and expand your
network. Let recruiters know you are open.
Subscribe to the Kaggle job listing. Jobs all
around the world.
Register in Getonboard website and look for
jobs in the Data/Analytics and programming
categories.
Job search
L o o k f o r o p p o r t u n i t i e s

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Research is exploration and discovery.
It's investigating something that no
one knows or understands. Research is
creating new knowledge.
N e i l A r m s t r o n g
“