This document discusses Dr. Ana Peleteiro Ramallo's career journey in data science and machine learning. It provides an overview of her educational and professional background, moving from academia to industry roles. It also highlights some key differences between academia and industry work, and discusses how machine learning and data science can be applied in the fashion retail industry for tasks like product forecasting, recommendations, search, and improving customer experience.

1. Living the AI era:
tales of Machine
Learning and data
DR. ANA PELETEIRO RAMALLO
Data Science Director, Tendam
@PeleteiroAna

2. I have always had a passion for
science, problems and data.
I am driven by innovation and
business value.

3. Telecommunications Engineering,
University of Vigo (2004-2009)
MsC. Thesis in KU Leuven,
COSIC Privacy Group,
Belgium (2009)
PhD in A.I.
(2010-2014)
Air Traffic
Controller
2 years of
Medicine
PostDoc,
University of
Vigo (2014)
Do I want to stay
in academia? No
Data Scientist
(Eagle Alpha)
(2015)
Senior Data Scientist
(2015)
Let’s figure out
what I want
now
I am not busy enough...
Free time? Basket
player
@CeltaVigo!
IIIA-CSIC-
Barcelona
King’s College
London
Data Science Director (Tendam,
previously Grupo Cortefiel) (2018)
Data Scientist of the
Year Ireland (2017)
Extraordinary
PhD award
WHO AM I AND HOW DID I GET HERE?
WiMLDS Madrid Co-
founder

4. Academia life Industry life
Advance science Delivery
Production and scalability? What is that? Production, scalability and real customers
Optimize results 1% is worth a year Iterate quickly and generate value rapidly: quality
vs time of delivery
Publish in the best conferences and journals Build products that you customers love and have
business impact
Research about whatever you want R&D oriented to products and having business
impact
My code is my code Code excellence and engineering practices
Not so much in contact with industry (although
more and more)
In touch with the state of the art, but balance it
with delivery
Sharing everything you do Sharing…some things
SOME DIFFERENCES BETWEEN ACADEMIA AND INDUSTRY

5. HOW CAN AI AND DATA HELP MY
COMPANY?

6. FASHION IS COMPLEX
AND CHALLENGING.
RELIED ON
EXPERIENCE
AND INTUITION

7. DATA
COMPUTING
TECHNOLOGIES

8. ML HAS MANY APPLICATIONS IN FASHION RETAIL
ü Segmentation, personalization and targeting
ü Recommendations
ü Search
ü Supply and demand
ü Price optimization
ü Fraud
ü Customer support
ü Logistics
ü Many more

9. El Pais
Without MACHINE LEARNING (ML), we could never keep up with the amount of
fashion resources that are available.

10. Qualitative Quantitative
Data driven decisions
Customer experience
DATA and ML help
to understand
fashion?

11. Pantone
Icon
PRODUCT FORECASTING IS A VERY COMPLEX PROBLEM

13. ML
Trends
RECOMMENDER SYSTEMS HAVE BECOME A MUST IN RETAIL

14. How can I help you
today?
I was wondering
what is trending
this spring
This spring is all about
new wave slip, in for
example jumpsuits
Is that
appropriate for a
work dinner?
Yes, it totally works! I
would recommend you
to use this chilly oil
jumpsuit. You can
combine it with a dark
brown belt and
cherry tomato heels.
All from Pedro del
Hierro
That sounds
great! Pedro del Hierro SS18
AI CAN ALSO HELP TO IMPROVE YOUR STYLE

15. VISUAL SEARCH IMPROVES USER EXPERIENCE

16. SOME OF MY CAREER ADVICES
ü Do things that you like
ü Never stop learning, read a lot! There are plenty
of free resources
ü Surround yourself with smart and curious people,
people from whom you can learn.
ü There is (almost) nothing that you can’t do
ü Look for feedback and give constructive
feedback.
ü Sometimes things are not going to work at first,
be perseverant.
ü Work with a good leaders/supervisors/bosses.

17. THANKS!
DR. ANA PELETEIRO RAMALLO
Data Science Director @TendamRetail
@PeleteiroAna