In this episode of DataFramed, Adel speaks with Barr Moses, CEO, and co-founder of Monte Carlo on the importance of data quality and how data observability creates trust in data throughout the organization.  Throughout the episode, Barr talks about her background, the state of data-driven organizations and what it means to be data-driven, the data maturity of organizations, the importance of data quality, what data observability is, and why we’ll hear about it more often in the future. She also covers the state of data infrastructure, data meshes, and more.  Relevant links from the interview: Connect with Barr on LinkedInLearn more about data meshesCheck out the Monte Carlo blogDataCamp's Guide to Organizational Data Maturity

In this episode of DataFramed, Adel speaks with Sergey Fogelson, Vice President of Data Science and Modeling at Viacom on how data science has evolved over the past decade, and the remaining large-scale challenges facing data teams today. Throughout the episode, Sergey deep-dives into his background, the various projects he’s been involved with throughout his career, the most exciting advances he’s seen in the data science space, the largest challenges facing data teams today, best practices democratizing data, the importance of learning SQL, and more.  Relevant links from the interview: Connect with Sergey on LinkedInCheck out Sergey’s course on DataCampLearn more about AirflowLearn more about PySparkLearn more about SQL More resources from DataCamp Upskill your team with DataCampOur Guide on Open Source Software in Data ScienceYour Organization’s Guide to Data Maturity

In this episode of DataFramed, Adel speaks with Dan Becker, CEO of decision.ai and founder of Kaggle Learn on the intersection of decision sciences and AI, and best practices when aligning machine learning to business value. Throughout the episode, Dan deep-dives into his background, how he reached the top of a Kaggle competition, the difference between machine learning in a Kaggle competition and the real world, the role of empathy when aligning machine learning to business value, the importance of decisions sciences when maximizing the value of machine learning in production, and more.  Links: Follow Dan on TwitterFollow Dan on LinkedInWhat 70% of data science learners do wrongCheck out Dan’s course on DataCampdecision.aiDan’s climate dashboard

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 LinkedInFollow Amen on TwitterThe New York City Business AtlasHurricane Sandy FEMA After-Action ReportData Drills

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: For the rest of April, get free access to DataCamp.Get involved with DataCamp Donates

Before the COVID-19 crisis, we were already acutely aware of the need for a broader conversation around data privacy: look no further than the Snowden revelations, Cambridge Analytica, the New York Times Privacy Project, the General Data Protection Regulation (GDPR) in Europe, and the California Consumer Privacy Act (CCPA). In the age of COVID-19, these issues are far more acute. We also know that governments and businesses exploit crises to consolidate and rearrange power, claiming that citizens need to give up privacy for the sake of security. But is this tradeoff a false dichotomy? And what type of tools are being developed to help us through this crisis? In this episode, Katharine Jarmul, Head of Product at Cape Privacy, a company building systems to leverage secure, privacy-preserving machine learning and collaborative data science, will discuss all this and more, in conversation with Dr. Hugo Bowne-Anderson, data scientist and educator at DataCamp.Links from the show FROM THE INTERVIEW Katharine on TwitterKatharine on LinkedInContact Tracing in the Real World (By Ross Anderson)The Price of the Coronavirus Pandemic (By Nick Paumgarten)Do We Need to Give Up Privacy to Fight the Coronavirus? (By Julia Angwin)Introducing the Principles of Equitable Disaster Response (By Greg Bloom)Cybersecurity During COVID-19 ( By Bruce Schneier)

This week, Hugo speaks with Sean Law about data science research and development at TD Ameritrade. Sean’s work on the Exploration team uses cutting edge theories and tools to build proofs of concept. At TD Ameritrade they think about a wide array of questions from conversational agents that can help customers quickly get to information that they need and going beyond chatbots. They use modern time series analysis and more advanced techniques like recurrent neural networks to predict the next time a customer might call and what they might be calling about, as well as helping investors leverage alternative data sets and make more informed decisions. What does this proof of concept work on the edge of data science look like at TD Ameritrade and how does it differ from building prototypes and products? And How does exploration differ from production? Stick around to find out. LINKS FROM THE SHOW DATAFRAMED GUEST SUGGESTIONS DataFramed Guest Suggestions (who do you want to hear on DataFramed?) FROM THE INTERVIEW Sean on TwitterSean's WebsiteTD Ameritrade Careers PagePyData Ann Arbor MeetupPyData Ann Arbor YouTube Channel (Videos)TDA Github Account (Time Series Pattern Matching repo to be open sourced in the coming months)Aura Shows Human Fingerprint on Global Air Quality FROM THE SEGMENTS Guidelines for A/B Testing (with Emily Robinson ~19:20) Guidelines for A/B Testing (By Emily Robinson)10 Guidelines for A/B Testing Slides (By Emily Robinson) Data Science Best Practices (with Ben Skrainka ~34:50) Debugging (By David J. Agans)Basic Debugging With GDB (By Ben Skrainka)Sneaky Bugs and How to Find Them (with git bisect) (By Wiktor Czajkowski)Good logging practice in Python (By Victor Lin) Original music and sounds by The Sticks.

This week, Hugo speaks with Debbie Berebichez about the importance of critical thinking in data science. Debbie is a physicist, TV host and data scientist and is currently the Chief Data Scientist at Metis in NY.In a world and a professional space plagued by buzz terms like AI, big data, deep learning, and neural networks, conversations around skill sets and less than productive programming language wars, what has happened to critical thinking in data science and data thinking in general? What type of critical thinking skills are even necessary as data science, AI and machine learning become even more present in all of our lives and how spread out do they need to be across organizations and society? Listen to find out!LINKS FROM THE SHOW DATAFRAMED GUEST SUGGESTIONS DataFramed Guest Suggestions (who do you want to hear on DataFramed?) FROM THE INTERVIEW Debbie on TwitterDebbie's WebsiteDebbie Berebichez- Media Reel (Video)Deborah Berebichez' Keynote at Grace Hopper Celebration 2017 (Video)Debbie Berebichez on Perseverance and Paying it Forward (Video)Things about the Future and the Future of Things (By Debbie Berebichez, Video) FROM THE SEGMENTS Data Science tools for getting stuff done and giving it to the world (with Jared Lander ~21:55) Lander Analytics WebsiteDocker Websiteplumber Website Statistical Distributions and their Stories (with Justin Bois ~39:30) Probability distributions and their stories (By Justin Bois)The History of Statistics (By Stephen M. Stigler)The Evolution of the Normal Distribution (By Saul Stahl) Original music and sounds by The Sticks.

This week, Hugo will be speaking with Skipper Seabold about the current and looming credibility crisis in data science. Skipper is Director of Data Science at Civis Analytics, a data science technology and solutions company, and also the creator of the statsmodels package for statistical modeling and computing in python. Skipper is also a data scientist with a beard bigger than Hugo's. They’re going to be talking about how data science is facing a credibility crisis that is manifesting itself in different ways in different industries, how and why expectations aren’t met and many stakeholders are disillusioned. You’ll see that if the crisis isn’t prevented, the data science labor market may cease to be a seller’s market and we’ll have big missed opportunities. But this isn’t an episode of Black Mirror so they’ll also discuss how to avoid the crisis, taking detours through the role of randomized control trials in data science, the rise of methods borrowed from econometrics and how to set realistic expectations around what data science can and can’t do.LINKS FROM THE SHOW DATAFRAMED GUEST SUGGESTIONS DataFramed Guest Suggestions (who do you want to hear on DataFramed?) FROM THE INTERVIEW Skipper on TwitterSkipper on GithubWhat's the Science in Data Science? (Video by Skipper Seabold)The Credibility Revolution in Empirical Economics: How Better Research Design Is Taking the Con out of Econometrics (By Joshua D. Angrist & Jörn-Steffen Pischke, American Economic Association)Project Management for the Unofficial Project Manager: A FranklinCovey Title (By Kory Kogon)Courtyard by Marriott Designing a Hotel Facility with Consumer-Based Marketing Models (Jerry Wind et al., The Institute of Management Sciences)Statsmodels's Documentation FROM THE SEGMENTS Guidelines for A/B Testing (with Emily Robinson ~15:48 & ~35:20) 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.

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 TwitterNoemi's WebsiteHuman Mobility Characterization from Cellular Network Data (By Richard Becker et al., Communications of the ACM)AT&T Labs Research WebsiteNASA Datanauts WebsiteOpen 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.