Data Scientists Thoughts that Inspire
Inspirational thoughts from leading data scientists, including Yann LeCun, Erin Shellman, Daniel Tunkelang, Claudia Perlich, and Jake Porway. What inspires you?
5. Roger Ehrenberg
Founder and Managing Partner of IA Ventures
- The biggest lesson is to have a very clear set of customers that you’re going to serve, notwithstanding the fact you may be building something that can ultimately help many different types of customers
6. Claudia Perlich
Chief Scientist at Dstillery (formerly Media6Degrees) and teaches data mining for business intelligence in the MBA program of the Stern School of Business, New York University
- Intuition develops with a lot of experience
- Data is the footprint of real life in some form, and so it is always interesting. It is like a detective game to figure out what is really going on
- The conversation is based around how to properly deal with even more sensitive information about where exactly people spend their lives
- So a large part of how things are presented, communicated, and represented carry very different messages from very different angles, depending on what you are reading, so you probably need a very broad depth to understand the issues
- My primary challenge as a data scientist is to use the right algorithm to connect the right data to the problem you actually want solved
- In the real world data is not like data they saw in classrooms and in books
- I prefer somebody who has done ten different things in ten different domains because they will have hopefully learned something new about data from each of different places and domains
- “Data scientist” is a completely undefined job description. Today, if you hire a data scientist, you do not know what you are getting
- Learning how to do data science is like learning to ski. You have to do it
7. Jonathan Lenaghan
Head of Data Science at PlaceIQ, a mobile geolocation intelligence company aggregating and analyzing spatial data for marketers
- People under pressure to find patterns are prone to fall into the common human fallacies of over insufficient data and over-reading correlation as causation.
- Losing somebody else’s money is one of the most horrible sinking feelings in the world
- Having no competitors is bad
- I always try to look at the problem from the end. When you start from the beginning and everything is blue sky, there are hundreds of ideas to chase as well as thousands of ideas to try and, since everything is possible, nothing ever gets done
- Keeping your eyes on the final deliverable is essential to solving the right problems
- Being self-critical is important
- Your location history that is important, not necessarily where you are right now
- It is very important to be self-critical: always question your assumptions and be paranoid about your outputs
8. Andre Karpistsenko
Co-Founder and Research Lead at Planet OS, a data discovery engine for sensor and machine data
- Conversations that happen in machines are different from the ones that happen in the physical world. In the physical world, it lasts a long time and we are able to use a lot of cues other than just text or audio. In computers, interactions are usually very short and many times there are many more people involved
- These days, if you build a community around yourself, the news and people start to find you
- Getting through life, through those uncertainties in a way, when you look back and see things still connect and exist, that’s the biggest measure of success
- There is a big part of intuition in choosing the most important problem.
- We are positioning ourselves to be lucky. We follow the adage that luck is being prepared for an opportunity and seizing it when it appears
- The core lesson from tool-and-method explorations is that there is NO silver bullet
- To build successful teams and projects, I strongly believe in the Kaizen approach. Kaizen was made famous in part by Japanese car manufacturers involved in continuous improvement. I believe you should always be looking for ways to improve things, just small things. Just try it out
- Financial gain is a second-order result: if you do the right things, everything else will follow.
- Maybe the most important thing is to surround yourself with people greater than you are and to learn from them
- The idea or the initial enthusiasm is just a small part of doing something great
- Everyone is right, depending on the situation and context
9. Amy Heineike
Director of Mathematics at Quid, an intelligence platform that combines natural language processing, machine learning, network science, and data visualization
- Data science is already kind of a broad church
- The key is figuring out how you get those three things: the right problem, the right data, and the right methodology to meld
- There are a lot of different roles that are going under the name “data science” right now, and there are also a lot of roles that are probably what you would think of data science but don’t have a label yet because people aren’t necessarily using it
- In general, it’s very hard to hire people who are a complete package, who know what to do and how to do it
10. Victor Hu
Chief Data Scientist at Next Big Sound, an online music industry platform that tracks artist popularity and probability and fan behavior across social media, radio, and traditional sales channels as reported at a granular level by record labels
- One of the big challenges of being a data scientist that people might not usually think about - is that the results or the insights you come up with have to make sense and be convincing. The more intelligible you can make them, the more likely it is that your recommendations will be put into effect
- People are more interested in their projects because they have selected them
- Hiring data scientists is very exciting at this time because in some ways there are no established guidelines on how to do it. People have skills in so many different areas
- It is hard to know what you really need until you dig into it
11. Jake Porway
Founder and Executive Director of DataKind, a nonprofit dedicated to using data science to tackle the world’s biggest problems
- The world will be more effective if everyone can at least converse about data science
- Data scientists in the business world are all generally well-compensated
- Data scientists can apply their skills for good
- Data is new eyes
- Data science is a way to see the world through the lens of this new macroscope to learn the patterns of society and nature so we can all live better lives
- There’s almost no limit to where data and data science can be applied
- Every company has data that can help make the world a better place
Bio: Andy Rey is a Ukrainian PhD Scientist interested in Marketing Data Research based on Data Mining & Machine Learning Techniques. He blogs at Happy Data Scientist.
Original.
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