Data Science Interview with David Suárez – Data Scientist at Apiumhub

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We are continuing with our interview series (previously we had interviewed Diego Ojeda – Android Lead at Apiumhub,  Serhii Zabolennyi – QA Automation engineer at ApiumhubJavier Gomez – backend developer at Apiumhub, Cuong Le – Backend developer at Apiumhub & Oriol Saludes – Fullstack Developer at Apiumhub. Today we interview David Suárez – Data Scientist at Apiumhub and talk about key lessons learned in Data Science.

Top 3 lessons learned in Data Science

 – No data, no glory

 – Maths are your friends

 – Good data, good results

What are the top 3 challenges in Data Science

– Show the potential of the data treatment

 – Break the barrier between the software and data science to make them work hand by hand.

 – Lead the IA on the road to make others lifes easier.

What are your top 3 tips for a Data Scientist? 

– Analyse the status of the data before starting to work with it in order to avoid wasting time looking for the mistake in the algorithm.

  Getting Started with Pandas - Lesson 1

– If something is going wrong or something has stopped you, just ask for help. It is always a good idea to count with your mate’s opinion.

– Focus on the scalability, it’s not just about the precision.

What advice would you give for junior data scientists who are hoping to grow professionally in this field?

Find a work team that matches your personality and where everyone wants to learn and teach to each other. That’s the best way to improve yourself and enjoy the time you spend working on the projects.

What are the top 3 responsibilities of a Data Scientist? 

– Use AI to improve people’s lives.

– Open the data science world to everyone who is interested in learning something about it.

– Get the maximum result from the data you have.

What are your insights/predictions in terms of Data Science?

This area is going to grow up so fast and has a lot of developments and innovation new systems that could be applied in different ways, not just in the business companies, where in a few years will be essential, but also in our culture and society, where we will see it reflected in smaller things. 

How do you deal with the unexpected as a Data Scientist?

We have to be patient and accept that sometimes the best data result is not enough and we have to look for other ones to reach them.

Do you have any favorite books or authors?

Reinforcement Learning: An Introduction a book by Andrew Barto and Richard S. Sutton

  What is Dimensionality Reduction?

How important is the culture of technology to you?

Essential. I am also used to applying it in a lot of aspects of my personal life.

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