Meet: Allen Ko is a data science manager working at States Title, where he's leading the company's efforts to automate document processing and parsing. He has a bachelor's degree in Chemical Engineering and loves to spend his free time hiking and wandering in the outdoors.

What you’ll learn:

Transitioning to the data industry via Metis

Stepping up to a manager role

More integration with the product team

If you have any questions for Allen, please feel free to reach out to him via LinkedIn:

https://www.linkedin.com/in/allenwko/

Meet: Connan has a strong background in Economics with his Ph.D. and has also taught at UCLA as a professor. He was a Data Scientist at Uber for over 4 years before taking over the Data Science team at Just Auto Insurance.

What you’ll learn:

Hiring for your Data team - a balanced team for success

Future of Data Scientists - evolving requirements and technical skills

Customer Lifetime Value (LTV) - an example from Uber

If you have any questions for Connan, please feel free to reach out to him via LinkedIn:

https://www.linkedin.com/in/connan-snider-4249311b/

Meet: Anson Whitmer - Head of Data. After completing a Ph.D., then a post-doc at Stanford, in cognitive neuroscience, Anson transitioned into data science.   He is now the director of data at Calm, a company that he help build up, as the first data hire, to its current unicorn+ status

What you’ll learn:

Fueling growth by discovering a new uses case for a product

Employe number 10 and first data hire

Prioritization - Focusing on delivering the most value for the business

If you have any questions for Anson, please feel free to reach out to him via:

https://www.linkedin.com/in/ansonwhitmer/

http://www.ansonwhitmer.com/

Meet: Daniel Gremmell is the Head of Data at Policygenius where he leads data engineering, data analysis, and data science. Before Policygenius, he was VP of Data Science at Plated. Daniel has experience in numerous industries including automotive, aerospace, and publishing. Daniel holds 2 master's degrees including an MS in Statistics from Rochester Institute of Technology.

What you’ll learn:

Finding ways to identify new requirements

Importance of having accurate views of the job and company you will be joining

Evaluating soft skills through virtual interviewing

If you have any questions for Dan, please feel free to reach out to him via LinkedIn:

www.linkedin.com/in/daniel-gremmell-6953842b

Meet: Peter has held management-level positions at Hearst and Freestar, before landing at Teachable, where he is the Head of Data. He also has his MBA from NYU.

What you’ll learn:

Building your data science team - case study and lessons learned

3rd party applications - pros/cons and the debate, to build in-house or buy

If you have any questions for Peter, please feel free to reach out to him via LinkedIn:

https://www.linkedin.com/in/peter-jaffe-4b18a66/

Meet: Marnie Benney is an Independent Curator working at the juncture of contemporary art and technology. Over the last decade, she has produced 27 exhibitions in city centers, public spaces, galleries, and festivals around the world including the New York Hall of Science, University of Cambridge London, the National Aquarium in Maryland, and The Nook Gallery in Los Angeles. Benney is the Co-founder and Curator of AIArtists.org, the world’s largest community of artists using Artificial Intelligence, where she provides a platform for artists to share their practice and investigate the future implications of AI on society.

What you’ll learn:

The impact of AI in Art

Technology mixing with art is not something new (see da Vinci)

Art has always pushed the envelope

If you have any questions for Marnie, please feel free to reach out to her via::

http://www.marniebenney.com/

https://www.instagram.com/marniebenney/

https://www.linkedin.com/in/marniebenney/

Some of the artwork/links discussed in the podcast:

https://aiartists.org/

http://bensnell.io/

http://www.saparcontemporary.com/

http://www.saparcontemporary.com/exhibitions#/art-andai

Meet: Bryan has worked at Facebook and Indeed on the Data Science and Machine Learning teams. He’s currently the Data Science Manager at Nextdoor.

What you’ll learn:

Grad School - the pros and cons and what you can do to jumpstart your career

Remote work - the pros and cons

If you have any questions for Bryan, please feel free to reach out to him via LinkedIn:

https://www.linkedin.com/in/bryangilbertdavis/

Meet: Josh Scott, an experienced security leader that focuses on building high performing and innovative security programs that are business-focused. Passionate about delivering security solutions that are maintainable, deliver value to the organization, and are as transparent as possible to customers both internal and external. More than 20 years of security experience in many security and technology domains and across various industries.

What you’ll learn:

Getting away from evaluating 3rd party tools and start building your own tools

The evolving relationship with other engineering departments

Find a small pilot project to begin shifting security left

If you would like to reach out to Josh about anything he discussed on the podcast, please reach out to him via LinkedIn or Twitter:

https://www.linkedin.com/in/joshuascott/

https://twitter.com/joshuascott94

Meet: Sean has worked at Google and Facebook. He was a Data Science Manager at Facebook working on the VR team before moving over to Goodwater Capital as their Data Science Manager.

What you’ll learn:

Data Moat - insight collection, defining success, operationalizing data applications

Showing your value - examples for data scientists to show their value

If you have any questions for Sean, please feel free to reach out to him via LinkedIn:

https://www.linkedin.com/in/shunpochang/

Meet: Clare Corthell is an entrepreneur and product manager in mapping and data science. She founded companies in drone mapping, data science consulting, and consumer ridesharing. She started the Open Source Data Science Masters, used as the blueprint for university accredited degrees since 2014. She is currently the Product Manager of map data at Lyft, hails from Stanford Engineering, and grew up in the wilds of Alaska.

What you’ll learn:

The relationship between product and data science

The risk of optimizing before doing experimentation

Data science of risk vs the data science of certainty

If you have any questions for Clare, please feel free to reach out to her via Twitter:

https://twitter.com/clarecorthell