#63 Set Yourself Multi-Year Professional Challenges with Felipe Flores – Founder & Podcast Host

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In this episode, Anthony Ugoni, one of Australia’s more prominent leaders in analytics interviews Felipe. Felipe came to Australia as a backpacker and ended up falling in love with the place. With Spanish as his first language, the only English he could say was the jacket is black. Then, Felipe explains some of his odd jobs and working freelance IT. At university, Felipe wanted to specialize in data, but all of his friends told him it was dead. So, he ended up specializing in hardware, even though all of his work was in data. When Felipe went to do his thesis, he happened to stumble into a project involving brain wave activity. The electrical engineer did all the research and design, the signals would be passed to Felipe’s computer, where he made his first application of machine learning. 

Then, Felipe explains how he and a colleague of his made the decision to quit their jobs at a small consulting firm. They decided to start their own firm, despite knowing very little about business. The first year they almost went bankrupt about four times and made lots of mistakes. They wanted to be in analytics but were unsure how to sell their services. The two spent six months creating a piece of software. When they went to show prospects they found out people did not like the entire product. So they decided to focus on their consulting business. 

After gaining so many clients, Felipe was literally sleeping in the office and billing over 100 hours each week. Coming up with solutions for the customers needed to be part of the sales process. Do exactly what the customer needs, and do it very quickly to build trust. Although you may be able to do even more for the customers to advance their businesses, target their needs first. After three trusted transactions with the customer, your relationship is built on trust, and then you can start recommending different projects. Eventually, Felipe went back to some of the people who expressed interest in investing in the company over the years and said they had an opportunity to invest. His partner got 51%, and Felipe sold his shares, the company is still going and has been rebranded. Later, Felipe discusses his work as the Executive Director & Head of Data Science at ANZ and explains their supportive work culture. Felipe also reveals the inspiration behind his podcast, Data Futurology, and describes his excitement behind explainable AI. 

Enjoy the show!

We speak about:

  • [02:40] Felipe’s background 

  • [06:10] Education and specializations

  • [14:30] Quick delivery of value  

  • [17:20] A series of odd jobs and IT freelancing  

  • [24:20] Setting up his own consulting company  

  • [33:15] Highs and lows of Clear Blue Water

  • [37:30] Executive Director & Head of Data Science at ANZ

  • [47:55] Supportive and open culture at work 

  • [52:40] Understanding the business at a new job

  • [54:45] Inspiration behind Data Futurology

  • [62:00] Explainable AI 

Resources:

Felipe’s LinkedIn: https://www.linkedin.com/in/felipefloresanalytics/?originalSubdomain=au

Episode #21 Antony Ugoni: https://www.datafuturology.com/podcast/21

Quotes:

  • “If I’m an engineer, people will think I’m smart.”

  • “A colleague of mine and I decided to set up our own consulting company. Professionally, it was the best and worst thing I’ve ever done.”

  • “Sales is built on trust and a human connection.”

  • “I had not done a good job of being a leader and creating a culture.”

  • “How can we make data scientists today, the CEOs of tomorrow?” 

Now you can support Data Futurology on Patreon!

https://www.patreon.com/datafuturology

Thank you to our sponsors:

UNSW Master of Data Science Online: studyonline.unsw.edu.au

Datasource Services: datasourceservices.com.au or email Will Howard on will@datasourceservices.com.au

Fyrebox - Make Your Own Quiz!

Felipe Flores is based in Melbourne, Australia.

And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!

#58 Explainable AI by Felipe Flores

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Today we have a different type of episode, this is a presentation that Felipe did at the Chief Data and Analytics Officer Conference in Canberra, and it is on explainable AI. First, Felipe explains how Amazon used a secret AI recruiting tool that had a bias against women. Also, the U.S. government used an algorithm predicting how likely people in the criminal justice system would reoffend. What they found is that it targeted specific racial groups. The algorithm isn’t racist or sexist, the data is.

Regarding job applications, as your company scales up, the need to automate the process of looking at the applications becomes necessary. Sometimes, bias will creep into the automated decision-making algorithm. The bias can even be narrowed down to the person’s name. For example, somebody with name Felipe might get scored lower than somebody with the name Tyler. Lean into the inequality and predict the bias. You can plug in the CV information, and ask the algorithm to predict the person’s race and gender. Then, find out what key inputs they are flagging to determine this and remove them from the algorithm.

Then, Felipe explains how algorithms can tackle unstructured data approaches. When discussing images, an algorithm was able to correctly identify a wolf from a husky 5 out of 6 times. However, when uncovering how the algorithm determined which was which, it was merely looking at if the animal was in the snow or not. If the picture had snow in it, then it must be a wolf. To determine how this algorithm was functioning, Felipe used LIME - Local Interpretable Model-Agnostic Explanations. It works for classifications and came out of a study from MIT. Later, Felipe discusses using EL15 and how transparency is essential for the public to understand how the algorithms could affect them.

Enjoy the show!

We speak about:

  • [03:40] Large companies and their biases

  • [05:40] Racism and sexism is in our data

  • [08:45] Uncovering inputs of the bias

  • [10:45] Unstructured data approaches

  • [14:30] Using ELI5

  • [19:20] The right to an explanation

Quotes:

  • “We teach our algorithms on how to replicate our decisions.”

  • “The algorithms show the inequality that we have in the world today.”

  • “Explainable AI is more ethical in the sense that it is more transparent.”

  • “Explainable AI helps us avoid blunders and informs us how the algorithm perceives the data.”

Now you can support Data Futurology on Patreon!  

https://www.patreon.com/datafuturology 

Thank you to our sponsors: 

UNSW Master of Data Science Online: studyonline.unsw.edu.au 

Datasource Services: datasourceservices.com.au or email Will Howard on will@datasourceservices.com.au 

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Felipe Flores is based in Melbourne, Victoria, Australia.

And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!

#38 How To Build a World Class Data Science Team

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In this episode, I talk about data scientists and ways you can attract the best talent to your team. Instead of telling your employees what they can do better, make them curious as to what they could do better. Then, I reveal the three things to look for when analyzing your pool of applicants. Once you have your team, now what? Once you have a decent pay settled, I explain the three things you will need to have for a capable team. Later, I tell you the elements, as a manager, you should be doing as rarely as possible.

In This Episode:

• [02:45] How to attract data scientists to your team?

• [04:45] The three things to look for from your pool of applicants

• [07:05] Adversity; test how they would react 

• [11:00] Three things needed to run an effective team

• [18:00] Managers should be doing this as rarely as possible

Creating a Data Team Session Quotes:

1. “Create a learning environment and continually challenging projects to focus on their development.”

2. “People should be open-minded and willing to learn; I test this in two different ways.”

3. “A lot of people come with technical skills from other countries.”

4. “They had to code it live with about eight people watching them, no pressure!”

5. “You know the answer, and you want to tell them to get to the outcome quickly. That’s an urge you have to roll back and fight against.” 

6. “Purpose is really what gets us out of bed every day.”

7. “Make yourself redundant as quickly as possible.”

Resources Mentioned: 

Drive: The Surprising Truth About What Motivates Us

Connect:

Twitter - https://twitter.com/datafuturology

Instagram - https://www.instagram.com/datafuturology/

Facebook - https://www.facebook.com/datafuturology

 

Now you can support Data Futurology on Patreon! 

https://www.patreon.com/datafuturology

 

Thank you to our sponsors: 

UNSW Master of Data Science Online: studyonline.unsw.edu.au 

Datasource Services: datasourceservices.com.au or email Will Howard on will@datasourceservices.com.au 

Fyrebox - Make Your Own Quiz!

Felipe is based in Melbourne, Australia

And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. It really helps new data scientists find us. Thank you so much, and enjoy the show!

 

Kickstarting 2019 With A Look Back at 2018 (Part 2): Episodes 19 to 34

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A lot of listeners have asked what have been my takeaways from the 30+ discussions with the guests on this podcast so far. To launch 2019 I’ve done a look back at all episodes from 2018. This is part 2 where I discuss episodes 19 to 34.

I hope you enjoy my recollection of these conversations. I’d love to hear what were your favourite takeaways!

Connect:

Twitter - https://twitter.com/datafuturology

Instagram - https://www.instagram.com/datafuturology/

Facebook - https://www.facebook.com/datafuturology

 

Now you can support Data Futurology on Patreon! 

https://www.patreon.com/datafuturology

 

Thank you to our sponsors: 

UNSW Master of Data Science Online: studyonline.unsw.edu.au 

Datasource Services: datasourceservices.com.au or email Will Howard on will@datasourceservices.com.au 

Fyrebox - Make Your Own Quiz!

Felipe is based in Melbourne, Australia

And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. It really helps new data scientists find us. Thank you so much, and enjoy the show!

Kickstarting 2019 With A Look Back at 2018 (Part 1): Episodes 1 to 18

Kickstarting 2019 With A Look Back at 2018 (Part 1): Episodes 1 to 18

A lot of listeners have asked what have been my takeaway points from the 30+ discussions with the guests on this podcast so far. To launch 2019 I’ve done a look back at all episodes from 2018. This is part 1 where I discuss episodes 1 to 18.

I hope you enjoy my recollection of these conversations. I’d love to hear what were your favourite takeaways!

Connect:

Twitter - https://twitter.com/datafuturology

Instagram - https://www.instagram.com/datafuturology/

Facebook - https://www.facebook.com/datafuturology

 

Now you can support Data Futurology on Patreon! 

https://www.patreon.com/datafuturology

 

Thank you to our sponsors: 

UNSW Master of Data Science Online: studyonline.unsw.edu.au 

Datasource Services: datasourceservices.com.au or email Will Howard on will@datasourceservices.com.au 

Fyrebox - Make Your Own Quiz!

 

Felipe is based in Melbourne, Australia



And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. It really helps new data scientists find us. Thank you so much, and enjoy the show!

#24 Mistakes in Building a DS Capability by Felipe Flores

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This is a different type of episode! This episode is a presentation I recently did at a large financial services institution. I presented on 5 Mistakes and Lessons Learned in Driving Business Value with Data Science and the Cloud.

I talk about:
- Using Lean Startup and Design Thinking principles in Data Science
- The importance of staying close to your end customer and what that looks like in practice
- The difference between machine learning for machines and for humans
- What is the purpose of ML/AI and how you can bring that thinking into your organisation
- What using ML for humans looks like
- Using data from other areas
- Leverage the flexibility of the cloud

Questions:

How can I learn data science?

Online Courses:

  • John Hopkins Data Science Specialisation on Coursera

  • Machine Learning by Andrew Ng on Coursera

  • Springboard: online course with mentor - get $250 off http://bit.ly/df-sb


Slides below. 

Felipe is based in Melbourne, Australia

And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. It really helps new data scientists find us. Thank you so much, and enjoy the show!

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#8 Agile Data Science by Felipe Flores

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This is a different type episode! This is a recording of a presentation I did to about 300 data scientists in Melbourne, Australia. The theme of the night was Agile Data Science, a passion of mine. In this episode I cover:

- the productivity gains an individual and a team can gain using agile methods
- how agile is imperfect but very helpful
- how I've tweaked agile to fit data science and deliver value with my teams
- bust some of the main myths around agile, and much, much more!

I hope you enjoy the episode!

I am based in Melbourne, Australia and currently travelling for a few months!