DataFramed
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Top 10 DataFramed Episodes
Goodpods has curated a list of the 10 best DataFramed episodes, ranked by the number of listens and likes each episode have garnered from our listeners. If you are listening to DataFramed for the first time, there's no better place to start than with one of these standout episodes. If you are a fan of the show, vote for your favorite DataFramed episode by adding your comments to the episode page.
Speedily adopting new technologies can give your business a competitive advantage, but with so much happening in the world of generative AI, it's difficult to know what to adopt. In this episode, Richie chats to two venture capitalists to get their view on the global AI landscape, where we are in the AI hype cycle, and how to adopt AI tech. Beyond this, we explore Rocketship.vc's use of data and algorithms to make investment decisions in early-stage startups. If our previous episode’s deep dive into 2024’s data & AI trends with VC Tom Tunguz got you excited about how investors are looking at the market at the moment, then this episode is sure to do the same. This time, we have twice the insight, thanks to our two guests.
Madhu Shalini Iyer is a Managing Partner at Rocketship.vc, a Silicon Valley based fund investing globally. She was the Chief Data Officer of Gojek and helped grow the business into a $10 billion unicorn. In addition to being a board member, she started the Singapore office and played an active role in the strategy, new business development, and ‘data as a competitive advantage’. Prior to Gojek, Madhu was part of the founding team of Intuit’s Quickbooks Lending Platform. As the data science leader at Intuit, Madhu helped grow the platform to $300 million and holds 2 patents in the areas of user data augmented algorithms for financial inclusion. Madhu was also the Chief Data Officer for Ethoslending. There she built the underwriting platform and was responsible for all b2c revenue, resulting in $65 million gross market value per month. Madhu was further responsible for building and running the marketing team. Prior, Madhu was a partner at a $150m private equity fund, Stem Financial, in Hong Kong. She started her career as a senior data scientist with a leading think tank in Menlo Park, CA.
Sailesh Ramakrishnan is also a Managing Partner at Rocketship.vc. Prior to Rocketship.vc, Sailesh was CTO and co-founder of LocBox (acquired by Square), a startup focussed on marketing for local businesses. Sailesh worked with Anand and Venky at their previous startup Kosmix, and continued on to Walmart as a Director of Engineering at @WalmartLabs. Before jumping into the startup world, Sailesh worked as a Computer Scientist at NASA Ames Research Center. Sailesh earned his Bachelors degree in Civil Engineering from IIT Madras, his Masters degree in Construction Management from Virginia Tech and another Master degree in Intelligent Systems from University of Pittsburgh. He was a Ph.D. candidate in Artificial Intelligence at the University of Michigan.
In the episode, Richie, Madhu and Sailesh explore the generative AI revolution, categorizing generative AI tools, the impact of genAI across industries, investment philosophy and data-driven decision-making, the challenges and opportunities when investing in AI, future trends and predictions, regulatory and ethical considerations of AI, and much more.
Links Mentioned in the Show:
- Rocketship.vc
- [Course] Implementing AI Solutions in Business
- Related Episode: Inside Algorithmic Trading with Anthony Markham, Vice President, Quantitative Developer at Deutsche Bank
- Sign up to RADAR: AI Edition
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1 Listener
09/06/21 • 55 min
In this episode of DataFramed, we speak with Rick Scavetta and Boyan Angelov about their new book, Python and R for the Modern Data Scientist: The Best of Both Worlds, and how it dawns the start of a new bilingual data science community.
Throughout the episode, Rick and Boyan discuss the history of Python and R, what led them to write the book, how Python and R can be interoperable, the advantages of each language and where to use it, how beginner data scientists should think about learning programming languages, how experienced data scientists can take it to the next level by learning a language they’re not necessarily comfortable with, and more.
Relevant links from the interview:
- We’d love your feedback! Let us know which topics you’d like us to cover and what you think of DataFramed by answering this 30-second survey
- Check out Rick and Boyan’s book
- Check out Rick’s courses on DataCamp
- Check out Boyan's other books
- Connect with Rick on LinkedIn
- Connect with Boyan on LinkedIn
#56 Data Science at AT&T Labs Research
DataFramed
03/11/19 • 56 min
This week, Hugo speaks with Noemi Derzsy, a Senior Inventive Scientist at AT&T Labs within the Data Science and AI Research organization, where she does lots of science with lots of data.
They’ll be talking about her work at AT&T Labs Research, the mission of which is to look beyond today’s technology solutions to invent disruptive technologies that meet future needs. AT&T Labs works on a multitude of projects, from product development at AT&T, to how to combat bias and fairness issues in targeted advertising and creating drones for cell tower inspection research that leverages AI, ML and video analytics. They’ll be talking about some of the work Noemi does, from characterizing human mobility from cellular network data to characterizing their mobile network to analyze how its topology compares to other real social networks reported to understanding tv viewership, and how engaged people are in different shows. They’ll discuss what the future of data science looks like, whether it will even be around in 2029 and what types of skills would help you land a job in a place like AT&T Labs.LINKS FROM THE SHOW
DATAFRAMED GUEST SUGGESTIONS
- DataFramed Guest Suggestions (who do you want to hear on DataFramed?)
FROM THE INTERVIEW
- Noemi on Twitter
- Noemi's Website
- Human Mobility Characterization from Cellular Network Data (By Richard Becker et al., Communications of the ACM)
- AT&T Labs Research Website
- NASA Datanauts Website
- Open NASA Website
FROM THE SEGMENTS
Guidelines for A/B Testing (with Emily Robinson ~18:23 & ~36:38)
- Testing multiple statistical hypotheses resulted in spurious associations: a study of astrological signs and health (By Peter C. Austin et al., Journal of Clinical Epidemiology)
- From Infrastructure to Culture: A/B Testing Challenges in Large Scale Social Networks (By Ya Xu et al., LinkedIn Corp)
- Guidelines for A/B Testing (By Emily Robinson)
- 10 Guidelines for A/B Testing Slides (By Emily Robinson)
Original music and sounds by The Sticks.
#68 The Future of Responsible AI
DataFramed
08/09/21 • 45 min
In this episode of DataFramed, Adel speaks with Maria Luciana Axente, Responsible AI and AI for Good Lead at PwC UK on the state and future of responsible AI.Throughout the episode, Maria talks about her background, the differences & intersections between "AI ethics" and "Responsible AI", the state of responsible AI adoption within organizations, the link between responsible AI and organizational culture, what data scientists can do today to ensure they're part of their organization's responsible AI journey, and more. Relevant links from the interview:
- Connect with Maria on LinkedIn
- Kate Crawford's Atlas of AI
- 9 Ethical AI Principles for Organizations to Follow
- PwC's Responsible AI Toolkit
- Read our Data Literacy for Responsible AI White Paper
05/03/21 • 44 min
In this episode of DataFramed, Adel speaks with Amen Ra Mashariki, principal scientist at Nvidia and the former Chief Analytics Officer of the City of New York on how data science is done in government agencies, and how it's driving smarter cities all around us.
Throughout the episode, Amen deep-dives into the use-cases he worked on to make the city of New York smarter, how data science allows cities to become more reactive and proactive, the unique challenges of scaling data science in a government setting, the friction between providing value and data privacy and ethics, the state of data literacy in government, and more.
Links from the interview:
- Follow Amen on LinkedIn
- Follow Amen on Twitter
- The New York City Business Atlas
- Hurricane Sandy FEMA After-Action Report
- Data Drills
New DataFramed Episodes
DataFramed
04/26/21 • 15 min
We are super excited to be relaunching the DataFramed podcast. In this iteration of DataFramed, Adel Nehme, a data science educator at DataCamp, will uncover the latest thinking on all things data and how it’s impacting organizations through biweekly (once every two weeks) interviews and conversations with data experts from across the world.
Check out this snippet for a preview of what’s to come and for a short chat with DataCamp’s CEO Jonathan Cornelissen on where he thinks data science is headed and the major challenges facing data teams today.
Links:
08/23/21 • 52 min
In this episode of DataFramed, we speak with Brent Dykes, Senior Director of Insights & Data Storytelling at Blast Analytics and author of Effective Data Storytelling: How to Turn Insights into Action on how data storytelling is shaping the analytics space.
Throughout the episode, Brent talks about his background, what made him write a book on effective data storytelling, how data storytelling is often misinterpreted and misused, the psychology of storytelling and how humans are shaped to resonate with it, the role of empathy when creating data stories, the blueprint of a successful data story, what data scientists can do to become better data storytellers, the future of augmented analytics and data storytelling, and more.
Relevant links from the interview:
02/18/19 • 54 min
This week, Hugo speaks with Marco Blume, Trading Director at Pinnacle Sports. Marco and Hugo will talk about the role of data science in large-scale bets and bookmaking, how Marco is training an army of data scientists and much more. At Pinnacle, Marco uses tight risk-management built on cutting-edge models to provide bets not only on sports but on questions such as who will be the next pope? Who will be the world hot dog eating champion, who will land on mars first and who will be on the iron throne at the end of game of thrones. They’ll discuss the relations between risk management and uncertainty, how great forecasters are necessarily good at updating their predictions in the light of new data and evidence, how you can model this using Bayesian inference and the future of biometric sensing in sports betting. And, as always, much, much more.LINKS FROM THE SHOW
DATAFRAMED GUEST SUGGESTIONS
- DataFramed Guest Suggestions (who do you want to hear on DataFramed?)
FROM THE INTERVIEW
FROM THE SEGMENTS
Data Science Best Practices (with Ben Skrainka ~16:40)
- Python Debugging With Pdb (By Nathan Jennings)
- pdb Tutorial (Github)
- The Visual Python Debugger for Jupyter Notebooks You’ve Always Wanted (By David Taieb)
- Debugging with RStudio (By Jonathan McPherson)
- Basics of Debugging
Statistical Distributions and their Stories (with Justin Bois at ~36:00)
Original music and sounds by The Sticks.
#40 Becoming a Data Scientist
DataFramed
09/17/18 • 61 min
Hugo speaks with Renee Teate about the many paths to becoming a data scientist. Renee is a Data Scientist at higher ed analytics start-up HelioCampus, and creator and host of the Becoming a Data Scientist Podcast. In addition to discussing the many possible ways to become becoming a data scientist, they will discuss the common data scientist profiles and how to figure out which ones may be a fit for you. They’ll also dive into the fact that you need to figure out both where you are in terms of skills and knowledge and where you want to go in terms of your career. Renee has a bunch of great suggestions for aspiring data scientists and also flags several important pitfalls and warnings. On top of this, they'll dive into how much statistics, linear algebra and calculus you need to know in order to become an effective data scientist and/or data analyst.
Links from the show
FROM THE INTERVIEW Becoming a Data Scientist (Renée's Blog) Renée's Twitter Data Sci Guide (Data Science Learning Directory)
FROM THE SEGMENTS
Statistical Distributions and their Stories (with Justin Bois at ~19:20)
Justin's Website at Caltech Probability distributions and their storiesProgramming Topic of the Week (with Emily Robinson at ~43:20)
Categorical Data in the Tidyverse, a DataCamp Course taught by Emily Robinson. R for Data Science Book by Hadley Wickham (Factors Chapter) Inference for Categorical Data, a DataCamp Course taught by Andrew Bray. stringsAsFactors: An unauthorized biography (Roger Peng, July 24, 2015) Wrangling categorical data in R (Amelia McNamara & Nicholas J Horton, August 30, 2017)Original music and sounds by The Sticks.
10/04/21 • 50 min
In this episode of DataFramed, we speak with Syafri Bahar, VP of Data Science at Gojek about building high-performing data teams, and how data science is central to Gojek’s success.
Throughout the episode, Syafri discusses his background, the hallmarks of a high-performance data team, how he measures the ROI on data activities, the skills needed in every successful data team, what is the best organizational model for data mature organizations, how Covid-19 affected Gojek’s data teams, his thoughts on data literacy and governance, future trends in data science and AI, and why data scientists should sharpen their maths and machine learning skills in an age of increasing automation.
Relevant links from the interview:
- We’d love your feedback! Let us know which topics you’d like us to cover and what you think of DataFramed by answering this 30-second survey
- Gojek’s Data Blog
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FAQ
How many episodes does DataFramed have?
DataFramed currently has 277 episodes available.
What topics does DataFramed cover?
The podcast is about Podcasts, Technology and Business.
What is the most popular episode on DataFramed?
The episode title '#205 The 2nd Wave of Generative AI with Sailesh Ramakrishnan & Madhu Iyer, Managing Partners at Rocketship.vc' is the most popular.
What is the average episode length on DataFramed?
The average episode length on DataFramed is 47 minutes.
How often are episodes of DataFramed released?
Episodes of DataFramed are typically released every 7 days.
When was the first episode of DataFramed?
The first episode of DataFramed was released on Jan 15, 2018.
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