Sometimes we forget the humans behind the tech in our ever busy world. DSF is fortunate enough to know some incredible tech leaders across the world and has the privilege of hearing them present at our events. That being said, our Speaker Spotlight sets the stage to get to know our speakers on a more personal level and connect them with our growing community. Read the mini interview below!

About Leonel

Leonel is a Data Scientist with 12+ years’ experience in the field. His north star is to help organizations grow by the means of AI, data and science. He loves to work in multi-cultural teams which he had the chance to lead in Buenos Aires, Rio de Janeito, Dublin, and Madrid. He has worked in the Tech, Internet, Gaming, Travel, Financial Services, and retail industries. He is an experimentation and science advocate and enjoys A/B testing product features, marketing strategies, and revenue management initiatives, as well as building classification and predictive machine learning models used by product and marketing teams. He is mostly used to SQL, R and python. He is one of the founders of Project Robyn the #1 open-source Marketing Mix Modeling code on GitHub today.

How did you start out in your tech career?

I started as a data scientist in a startup for social gaming called Vostu. We were in charge of measuring and improving user engagement, monetization and LTV. It was the best learning experience as I had the chance to work with some of the best data scientists in my career from Silicon Valley, Argentina and Europe.

What are the signs of success in your field?

I believe that a good sign of success in the data science field in any company should embrace:
– Consultancy skills: asking the right questions and helping others to ask themselves the right questions, building a learning roadmap that can be proven by the means of science.
– Proving actual value, not just concepts: By applying science and asking ourselves the right questions we should be able to set a testing roadmap that can prove the actual business value of products or services implemented by the organization.
– Scientific rigor: Making observations, asking the right questions, testing and proving actual business value are parts of an iterative and well-structured scientific process. The key aspect along this process is understanding human bias and aiming to minimize it.
– Leadership and collaboration: Data science teams must work in a collaborative way and be embedded on day-to-day decision making across the organization. A good data science team should know the strategy and hypotheses behind the business in detail and should be one of the first to propose and think of alternatives that can answer key business questions.

What is the best and worst thing about your job role?

– The best: To be able to prove and help the leadership to decide which projects, products or services will dramatically improve an organization’s performance against a defined KPI. And, to use AI/ML in order to automate and enrich decision processes.
– The worst: To be able to gather, process and manipulate all the necessary data

What can you advise someone just starting out to be successful?

Well, I would first say, no pain no gain. Most of the learnings and successes in my career have been achieved by applying theory to actual practice. Secondly, you must persevere, in order to succeed. As a colleague of mine used to say, doing data science is not the same as delivering pizza, we actually have to understand all the nuances and nitty gritty details that can bring rigor and actual value to data-backed decision making. So, we are much better off with good quality analyses rather than with greater quantity.

How do you switch off?

Mostly by enjoying some quality time with my friends and family. I also enjoy my time alone at home and love to travel to new places I have never been to.

What advice would you give your younger self?

There will be times when you will think that you are not capable or good enough to do what you love or that you won’t be able to find the right job position where that can happen. Just be patient, keep trying and learn python 😄

What are your top 5 predictions in tech for the next 5 years?

– Privacy-enhancing technologies (PETs) such as blockchain, encryption and multi-party computation will be broadly used by businesses
– AI will permeate and influence human decision making, products and services offers in such a symbiotic way that we won’t even realize that we are using it.
– Augmented reality will start to show its ways through devices which will improve the user experience and shorten the gap between the universe and the metaverse.
– AI will contribute to automating tech processes such as coding design and any kind of digital creation.
– The componentization of software in mini-service applications and the increasingly distributed cloud-based hardware architecture will be increasingly accelerated.

Watch Leonel’s session at the Data Science Festival here.

Thank you to all our wonderful speakers for taking part in our Speaker Spotlight!

Want to become a DSF Speaker? Apply here!