Adam Sroka is the Head of Machine Learning Engineering at Origami Energy where he's helping build a green energy world. Their trading and automation software enables energy companies to harness the commercial opportunities of the global energy transition. He is an experienced AI leader helping organizations unlock value from data and build high-performing teams from the ground up. He shares his thoughts and ideas through public speaking, tech community events, and on his blog.

In this episode, we cover a range of topics including:
- how energy markets work
- renewable energy
- solving climate problems
- building teams
- why it's important for data scientists to know software engineering

Doug Laney is the Data & Analytics Strategy Innovation Fellow at West Monroe Partners. He consults to business, data, and analytics leaders on conceiving and implementing new data-driven value streams. He originated the field of infonomics and authored the best-selling book Infonomics. He is a three-time Gartner annual thought leadership award recipient, a World Economic Forum advisor, a Forbes contributing author, and co-chairs the annual MIT Chief Data Officer Symposium. He also is a visiting professor at the University of Illinois and Carnegie Mellon business schools, and sits on various high-tech company advisory boards.

In this episode, we cover a range of topics including:
- Infonomics 
- His latest book Data Juice 
- Quantifying data's economic value 
- Applying asset management principles to data management 
- Data monetization patterns 
- Collateralizing data 
- Underwriting and insuring the data asset 
- Testing ideas for feasibility 
- How to price data products 

In this episode, the host Prateek Joshi talks about:
- The question of whether AI is sentient
- Yann LeCun's recent proposal on Autonomous Machine Intelligence
- NASA's helicopter on Mars
- Amazon's AI-powered coding assistant
- A reconfigurable AI chip built by MIT engineers

Jason Krantz is the founder of Strategy Titan. Their offering simplifies workforce and compensation data so that businesses can confidently make hiring and retention decisions. He has access to a goldmine of data on talent trends and where the labor market is heading.

In this episode, we cover a range of topics including:
- Trends in the US labor market
- Talent trends in the AI sector
- Full time vs gig economy
- Flow of talent across sectors
- How can businesses leverage data on jobs and compensation to differentiate themselves
- Similarities and differences across hyperlocal job markets in US
- The craft of employee retention

Jordan Morrow is the VP of Data and Analytics at Brainstorm. He has been in data for a long time now across companies like Qlik and Pluralsight. He is a two-time winner of Data IQ100, a list of the most influential data and analytics practitioners. He has built expertise in the area of data literacy and upskilling.

In this episode, we cover a range of topics including:
- Data literacy
- Upskilling and reskilling
- Learning platforms for data professionals
- Where are the gaps in skills for data professionals
- Landscape of products for education and upskilling
- What's the next unlock for the education market

Harpreet Sahota is the host of The Artists of Data Science podcast. He's a data science generalist with a strong business acumen. He currently works on Developer Relations at Pachyderm where he is defining and executing strategies that demonstrate the value of data. 

In this episode, we cover a range of topics including:
- Building bottom up ML products
- Driving product adoption
- Building the DevRel function at a startup
- What makes an online community great
- How to create useful content
- Understanding the MLOps ecosystem
- Building a personal brand

Brent Dykes is the founder of Analytics Hero where he offers workshops on data storytelling. As a Forbes contributor, he has authored more than 45 articles and spoken at some of the largest industry conferences around the globe. After publishing two books on digital analytics, his most recent book focuses on the importance of effective data storytelling.

In this episode, we cover a range of topics including:
- Why do we need data storytelling
- What does storytelling entail
- Data, narrative, and visuals
- How to distill down complex topics
- Step by step process of building a practical data story

Joe Reis is a business-minded data engineer who’s worked in the industry for 20 years. He is the CEO and Co-Founder of Ternary Data, a data engineering and architecture consulting firm based in Salt Lake City, Utah. He volunteers with several technology groups and teaches at the University of Utah. In his spare time, he likes to rock climb, produce electronic music, and take his kids on crazy adventures.

In this episode, we cover a range of topics including:
- What does a data engineer do?
- Relationship between data engineering and MLOps
- What are the components of the data engineering lifecycle?
- What should a data engineer know at a fundamental level to be successful at this?
- His book Fundamentals of Data Engineering 
- Why writing a book is one of the few activities that exposes your weaknesses and very deeply refines your thinking
- The three pillars of a solid data foundation: data architecture, data engineering, and DataOps. 
- How do you structure your first call with a potential client? 
- Why is there a mismatch between expectations and reality when it comes to using data science within a business?
- Why he puts a lot of the responsibility on the student to get good at researching problems and solutions
- How to think about architecture as a data professional

In this episode, Prateek Joshi talks about the latest developments in:
- Using AI to build digital twins for nuclear fusion reactors
- Photonic chips for fast image recognition
- Electronic skin for touch sensitive robots
- Delivering brain MRI in 1 minute
- Using AI for energy grid management
- Analyzing satellite imagery using machine learning

Vin Vashishta is a globally recognized expert on AI Strategy and Data Science. He has been a LinkedIn Top Voice in Data Science and has been featured on dozens of Top 10 Lists over the last 7 years. His client list includes the likes of Walmart, JPMC, Siemens, and Airbus. He delivers products with recurring revenue streams in the 100s of millions and build Data Science teams from the ground up. He advises startups and teaches founders how to launch their first ML based product. He founded V-Squared in 2012 and built it into a successful AI Strategy consulting practice. 4 years ago, he started teaching Business Strategy For Data Scientists. 

In this episode, we cover a range of topics including:
- Teaching a strategy class for data scientists
- How to measure the success of data science projects
- How to identify the highest value opportunities
- You learn a lot by building ML models, but you learn more my maintaining them for 6 months. Why is that?
- What are transferable capabilities for a professional who wants to transition into data science?
- How to inject reality into ML products using domain knowledge?
- Advantages of rapid prototyping
- How to structure AI strategy sessions with potential new collaborators?
- What is career coaching?
- How to hire great data scientists?