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

Meet: Silvano has 20 years of experience in IT and Information Security and his interests include DevSecOps, AppSec, and business-driven risk-based approach. Silvano is a proponent of Security integrated into the product development lifecycle to create a seamless culture of security by design.

What you’ll learn:

Finding the right balance as a product-focused CISO

Compliance requirements as a part of selling into the enterprise space

Partner with developers earlier in the development process

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

https://www.linkedin.com/in/silvano-silva-7694833/

Meet: Jesse Lehmier is a data engineering manager at ASAPP. He previously worked in analytics, big data, and full-stack software engineering roles.

What you’ll learn:

Seize opportunities to develop soft skills

Transitioning from a software engineering role into data engineering

Don’t spin your wheels, ask for help sooner

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

https://linkedin.com/in/lehmier

Meet: Adam Oliner, Head of Machine Learning at Slack. Prior to Slack, Adam was leading the team at Splunk. He has his Masters and Ph.D. in Computer Science from Stanford and did his undergraduate degree at MIT.

What you’ll learn:

Commoditization of tooling - how it affects your career

Structuring your Machine Learning organization - best practices and approaches

Machine Learning Projects - how to get traction and how to think about your projects (failures and iterations)

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

https://www.linkedin.com/in/adam-oliner-b9a2b35a/

Meet: Rohit Vashisht is the co-founder and CEO of whiz.ai, a conversational AI platform for Life Sciences commercial ops and field teams. Previously, Rohit was CEO and co-founder of Sverve – an influencer marketplace that was acquired by Bloglovin’ and rebranded as Activate. Rohit holds an M.B.A from the NYU Stern School of Business and an engineering degree from I.I.T, Delhi.

What you’ll learn:

Why can't enterprise software be as easy to use as consumer software

Helping organizations answer questions simpler and faster

Leveraging AI to deliver answers faster to sales and ops teams in the field

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

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

https://twitter.com/_techCEO

Meet: Jeshua Bratman is an expert in building technology products powered by artificial intelligence. He’s a founding member of Abnormal Security and head of machine learning. Prior to joining Abnormal, Jeshua played a critical role in building Twitter’s machine learning platform and detecting and preventing abusive behavior on the Twitter product. Prior to Twitter, Jeshua built the AI engine that powered TellApart’s advertising product and bringing it to over $100 million ARR and acquisition by Twitter and integration. His academic experience is in theoretical reinforcement learning and deep learning at the University of Michigan.

What you’ll learn:

Machine learning driving business value

Email hackers against machine learning models - the chess match

Advice on how to find your next machine learning position

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

https://twitter.com/nojeshua

linkedin.com/in/jeshuabratman/

Meet: Gagan Sandhu, Sr. Engineering Director at Square. He leads the ML, Data Engineering and Mobile engineers within the e-commerce product division at Square.

What you’ll learn:

Machine Learning - How to apply ML effectively to your organization: from getting buy-in for projects, managing expectations, and solving the right problems by working with the right people.

Mentorship - Different strategies for different people and building trust as a leader. Keeping a pulse on your team and creating rituals for your team.

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

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