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Data science is one of the fastest growing industries and has been called the ‘Sexiest job of the 21st Century’. But what exactly is data science? In this podcast, brought to you by DataCamp, Hugo Bowne-Anderson approaches the question by exploring what problems data science can solve rather than defining what data science is. From automated medical diagnosis and self-driving cars to recommendation systems and climate change, come on a journey with experts from industry and academia to explore the industry that will change the course of the 21st century.

Episode Date
#35 Data Science in Finance
Hugo speaks with Yves Hilpisch about how data science is disrupting finance. Yves’ name is synonymous with Python for Finance and he is founder and managing partner of The Python Quants, a group focusing on the use of open source technologies for financial data science, artificial intelligence, algorithmic trading and computational finance. Why are banks such as Bank of America & JP Morgan adopting the open source data science ecosystem? What are the major sub-disciplines of Finance that data science is and can have a large impact in? How has the rise of data science changed the financial world and how the work is done and thought about? Stick around to find out.
Aug 13, 2018
#34 Data Journalism & Interactive Visualization
Hugo speaks with Amber Thomas about data journalism, interactive visualization and data storytelling. Amber is a journalist-engineer at The Pudding, which is a collection of data-driven, visual essays. We’ll discuss the ins and outs of what it takes to tell interactive journalistic stories using data visualization and, in the process, we’ll find out what it takes to be successful at data journalism, the trade-off between being being a generalist and specialist and much more. We’ll explore these issues by focusing on several case studies, including a piece that Amber worked on late last year called “How far is too far? An analysis of driving times to abortion clinics in the US.”
Aug 06, 2018
#33 Pharmaceuticals and Data Science
What are the biggest challenges in Pharmaceuticals that data science can help to solve? How are data science and statistics generally embedded in organizations such as Pfizer? What aspects of the pharmaceutical business run the gamut of nonclinical statistics? Hugo speaks with Max Kuhn, a software engineer at RStudio who was previously Senior Director of Nonclinical Statistics at Pfizer Global R&D. Max was applying models in the pharmaceutical and diagnostic industries for over 18 years.
Jul 30, 2018
#32 Data Science at Doctors without Borders
Hugo speaks with Derek Johnson, an epidemiologist with Doctors without Borders. Derek leverages statistical methods, experimental design and data scientific techniques to investigate the barriers impeding people from accessing health care in Lahe Township, Myanmar. If you thought data science was all machine learning, SQL databases and convolutional neural nets, this is gonna be a wild ride as to get the data for their baseline health assessments, Derek and his team ride motorcycles into villages in northern Myanmar for weeks on end to perform in person surveys, equipped with translators and pens and paper because they can’t be guaranteed of electricity. Derek also researches the factors associated with the transmission of hepatitis C between family members and has helped to conduct studies in Uganda, Nepal, and India. All this and more.
Jul 23, 2018
#31 Chatbots, Conversational Software & Data Science
Hugo speaks with Alan Nichol about chatbots, conversational software and data science. Alan is co-founder and CTO of Rasa, who build open source machine learning tools for developers and product teams to expand bots beyond answering simple questions. Which verticals are conversational software currently having the biggest impact on? What are the biggest challenges facing the fields of chatbots and conversational software? What misapprehensions do we as a society have about these technologies that experts such as Alan would like to correct? And how can we all build chatbots and conversational software ourselves?
Jul 16, 2018
#30 Data Science at McKinsey
Hugo speaks with Taras Gorishnyy, a Senior Analytics Manager at McKinsey and Head of Data Science at QuantumBlack, a McKinsey company. They discuss

  • the role of data science in management consulting,
  • what it takes to change organizations through data science,
  • how the different moving parts of data science have evolved over the past decade and in which direction they’re heading.

You’ll see the impact that data science can have not only in tech, but also in such various verticals as retail, agriculture and the penal system. Taras will also take us through the 5 steps required to change organizations through data science, all of which are necessary. Can you guess what they are? We're really excited to have Taras on the show as DataCamp has had a long relationship with McKinsey, including that McKinsey uses DataCamp for training.

Jul 09, 2018
#29 Machine Learning & Data Science at Github
Omoju Miller, a Senior Machine Learning Data Scientist with Github, speaks with Hugo about the role of data science in product development at github, what it means to “use computation to build products to solve real-life decision making, practical challenges” and what building data products at github actually looks like. Machine learning has the power to automate so much of the drudgery around data science & software engineering, from automated code review to flagging security vulnerabilities in code, and from recommending repositories to contributors to matching issues with maintainers and contributors and identifying duplicate issues. And just in case that’s not enough, they'll discuss github as a platform for work, not just technical, and, as Omoju has called it, “a collaborative work environment centered around humans.”
Jul 02, 2018
#28 Organizing Data Science Teams
What are best practices for organizing data science teams? Having data scientists distributed through companies or having a Centre of Excellence? What are the most important skills for data scientists? Is the ability to use the most sophisticated deep learning models more important than being able to make good powerpoint slides? Find out in this conversation with Jonathan Nolis, a data science leader in the Seattle area with over a decade of experience. Jonathan is currently running a consulting firm helping Fortune 500 companies with data science, machine learning, and AI.

Links from the show

Jun 25, 2018
#27 Data Security, Data Privacy and the GDPR
What are the biggest challenges currently facing data security and privacy? What does the GDPR mean for civilians, working data scientists and businesses around the world? Is data anonymization actually possible or a pipe dream? Find out in Hugo's conversation with Katharine Jarmul, a data scientist, consultant, educator and co-founder of KI protect, a company that provides real-time protection for your data infrastructure, data science and AI.

Links from the show

Jun 18, 2018
#26 Spreadsheets in Data Science
Why are spreadsheets ubiquitous in data analytics, why are so many data scientists anti-spreadsheet? Join Jenny Bryan, a software engineer at RStudio & recovering biostatistician who takes special delight in eliminating the small agonies of data analysis, and Hugo to discover why spreadsheets are in fact necessary in data analytics and how spreadsheet workflows can be incorporated into more general data science flows in sustainable and healthy ways. Welcome to the future.

Links from the show

Jun 11, 2018
#25 Data Science for Everyone
Community building is an essential aspect of data science. But how do you do it? Find out in Hugo's conversation with Jared Lander, organizer of the New York Open Statistical Programming Meetup and the New York R Conference. Jared is also the Chief Data Scientist of Lander Analytics, a data science consultancy based in New York City and an Adjunct Professor of Statistics at Columbia University. How does Jared think about creating safe and welcoming spaces for budding and practicing data scientists of all ilk? How does he put this into practice? How does he make people feel comfortable and at home in a field in which so many intelligent and curious people feel like imposters? What practical & specific considerations are there in creating this home for underrepresented groups? How does he stay ahead of the curve in terms of modern, up-to-date content and speakers for his meetup and conference?
Jun 04, 2018
#24 Data Science in the Cloud
"Cloud computing is a huge revolution in the computing space, and it's also probably going to be one of the most transformative technologies that any of us experience in our lifetime. " Paige Bailey, Senior Cloud Developer Advocate at Microsoft, in this episode of DataFramed. In this conversation with Hugo, Paige reports from the frontier of cloud-based data science technologies, having just been at the Microsoft Build and Google I/O conferences. What is the future of data science in the cloud? How can you get started? Stick around to find out and much, much more.
May 28, 2018
#23 Online Experiments at
What do online experiments, data science and product development look like at, the world’s largest accommodations provider? Join Hugo's conversation with Lukas Vermeer to find out. Lukas is responsible for experimentation at Booking in the broadest sense of the word: from Infrastructure and Tools used to run experiments, Methodology and Metrics that help people make decisions to Training and Culture that help people understand what to do. They'll be talking about how Booking leverages Data Science to help empower people to experience the world through the three pillars of exploratory analysis, qualitative research and quantitative studies. They'll also take a deep dive into the fact that data science isn't actually anywhere near as objective as you may think.
May 21, 2018
#22 Robust Data Science with Statistical Modeling
Building models of the world is dangerous and there are pitfalls everywhere, even down to the assumptions that you make. To find out about many statistical pitfalls, and how to build more robust data scientific models using statistical modeling, whether it be in tech, epidemiology, finance or anything else, join Hugo's chat with Michael Betancourt, a physicist, statistician and one of the core developers of the open source statistical modeling platform Stan.
May 14, 2018
#21 The Fight Against Cancer
How can data science help in the fight against cancer? What are its limitations? Find out in this conversation from the frontier of research. Hugo speaks with Sandy Griffith from Flatiron Health, a healthcare technology and services company focused on accelerating cancer research and improving patient care. Sandy is Principal methodologist on Flatiron's Quantitative Sciences team and is tasked with leveraging data science "To improve lives by learning from the experience of every cancer patient".
May 07, 2018
#20 Kaggle and the Future of Data Science
Anthony Goldbloom, CEO of Kaggle, speaks with Hugo about Kaggle, data science communities, reproducible data science, machine learning competitions and the future of data science in the cloud. If you thought that Kaggle was merely a platform for machine learning competitions, you have to check out this chat, because these ML comps account for less than a third of activity on Kaggle today. In the discussion: Kaggle kernels for reproducible data science and the evolution of the Kaggle public data platform; the genesis of Kaggle and how Anthony managed to solve the cold start problem of building a two-sided market place; the exciting implications of Kaggle's recent acquisition by Google for the future of cloud-based data science; why Python is dominant on Kaggle.
Apr 30, 2018
#19 Automated Machine Learning
"We should be looking at Automated Machine Learning tools as more like data science assistants, rather than replacements for data scientists" -- Randy Olson, Lead Data Scientist at Life Epigenetics, Inc. Randy specializes in artificial intelligence, machine learning, and created TPOT, a Data Science Assistant and a Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming. Will the future of data science be automated? Which verticals will experience the largest disruption? What will the role of data science become? There's one way to find out: jump straight into this chat with Randy and Hugo.
Apr 23, 2018
#18 Deep Learning at NVIDIA
Michelle Gill, a deep learning expert at NVIDIA, an Artificial Intelligence company that builds GPUs, the processors that everybody uses for deep learning, speaks with Hugo about the modern superpower of deep learning and where it has the largest impact, past, present and future, filtered through the lens of Michelle's work at NVIDIA. Where is the modern superpower of deep learning most effective? Where is it not? Where should we channel our skepticism of the hype surrounding it?
Apr 16, 2018
#17 Biology and Deep Learning
Sebastian Raschka, a machine learning aficionado, data analyst, author, python programmer, open source contributor, computational biologist, and occasional blogger, speaks with Hugo about the role of data science in modern biology and the power of deep learning in today's rapidly evolving data science landscape. How is Sebastian using deep learning to build facial recognition software that also prevents racial and gender profiling? Check out this week's episode to find out.
Apr 09, 2018
#16 Data Nerdism at Large
Mara Averick, self-labelled data nerd and Tidyverse developer advocate at RStudio, speaks with Hugo about all things data: what it means to be a data nerd and how data science impacts all of our lives from thinking about toxicology to sports analytics to data for social good and civic tech; how can thinking about data make you a better citizen and how can we design computational interfaces to meet humans where they are? How we can help everybody access data relevant to them?
Apr 02, 2018
#15 Building Data Science Teams
Drew Conway, world-renowned data scientist, entrepreneur, author, speaker and creator of the Data Science Venn Diagram speaks with Hugo about how to build data science teams, along with the unique challenges of building data science products for industrial users. How does Drew now view the Venn circles he created, those of hacking skills, mathematical and statistical knowledge and substantive expertise, when building out data science teams?
Mar 26, 2018
#14 Text Mining and Natural Language Processing in Data Science
How can data science be leveraged to inform business decisions around all the text data that businesses have and what can text mining all the open text data out there tell us about society? For example, what can analyzing film scripts tell us about gender dynamics in Hollywood? Join Julia Silge, data scientist at Stack Overflow, as she takes a deep dive with Hugo into data science, the written word, text mining and natural language processing.
Mar 19, 2018
#13 Fake News Detection with Data Science
Fake news: how can data science and deep learning be leveraged to detect it? Come on a journey with Mike Tamir, Head of Data Science at Uber ATG, who is building out a data science product that classifies text as news, editorial, satire, hate speech and fake news, among others. We'll also see what types of unique challenges Mike faced in his work at Takt, using data science to service the needs of Fortune 500 companies such as Starbucks.
Mar 12, 2018
#12 Data Science, Nuclear Engineering and the Open Source
Nuclear engineering, data science and open source software development: where do these all intersect? To find out, join Hugo and Katy Huff, Assistant Professor in the Department of Nuclear, Plasma, and Radiological Engineering at the University of Illinois where she leads the Advanced Reactors and Fuel Cycles research group.
Mar 05, 2018
#11 Data Science at BuzzFeed and the Digital Media Landscape
How does data science help Buzzfeed achieve online virality? What type of mass online experiments do data scientists at BuzzFeed run for this purpose? What products do they develop to make all of this easy and intuitive for content producers? Find out about all of this and more in this episode when Hugo talks with Adam Kelleher, Principal Data Scientist at BuzzFeed and Adjunct Assistant Professor at Columbia University. They'll also dive into the role of thinking about causality in modern data science.
Feb 26, 2018
#10 Data Science, the Environment and MOOCs
Air pollution, the environment and data science: where do these intersect? Find out in this episode of DataFramed, in which Hugo speaks with Roger Peng, Professor in the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health, co-director of the Johns Hopkins Data Science Lab and co-founder of the Johns Hopkins Data Science Specialization. Join our discussion about data science, it's role in researching the environment and air pollution, massive open online courses for democratizing data science and much more.
Feb 19, 2018
#9 Data Science and Online Experiments at Etsy
Etsy, online experiments and data science are the topics of this episode, in which Hugo speaks with Emily Robinson, a data analyst at Etsy. How are data science and analysis integral to their business and decision making? Join us to find out. We'll also dive into the types of statistical modeling that occurs at Etsy and the importance of both diversity and community in data science.
Feb 12, 2018
#8 Data Science, Astronomy and the Open Source
Jake VanderPlas, a data science fellow at the University of Washington's eScience Institute, astronomer, open source beast and renowned Pythonista, joins Hugo to speak about data science, astronomy, the open source development world and the importance of interdisciplinary conversations to data science.
Feb 05, 2018
#7 Data Science at Airbnb
Airbnb's business depends on data science. In this episode, Hugo speaks with Robert Chang, data scientist at airbnb and previously at twitter. We'll be chatting about the different types of roles data science can play in digital businesses such as airbnb and twitter, how companies at different stages of development actually require divergent types of data science to be done, along with the different models for how data scientists are placed within companies, from the centralized model to the embedded to the hybrid: can you guess which is Robert's favourite? This is a hands-on, practical look at how data science works at airbnb and digital businesses in general.
Jan 29, 2018
#6 Citizen Data Science
David Robinson, a data scientist at Stack Overflow, joins Hugo to speak about the evolving importance of citizen data science and a future in which data literacy is considered a necessary skill to navigate the world, similar to literacy today. We'll speak about many of Dave projects, including his analysis of Trump's tweets that demonstrated the stark contrast between Trump's own tweets and those of his PR machine. We'll also speak about ways for journalists, software engineers, scientists and all walks of life to get up and running doing data science and analysis.
Jan 17, 2018
#5 Data Science, Epidemiology and Public Health
Maelle Salmon, a data scientist who has worked in public health, both in infectious disease and environmental epidemiology, joins Hugo for a chat about the role of data science, statistics and data management in researching the health effects of air pollution and urbanization. In the process, we'll dive into the continual need for open source toolbox development, open data, knowledge organisation and diversity in this emerging discipline.
Jan 17, 2018
#4 How Data Science is Revolutionizing the Trucking Industry
The trucking industry is being revolutionized by Data Science. And how? Hugo speaks with Ben Skrainka, a data scientist at Convoy, a company that provides trucking services for shippers and carriers powered by technology to drive reliability, transparency, efficiency, and insights. We'll dive into how data science can help to achieve such a trucking revolution, and how this will impact all of us, from truckers to businesses and consumers alike. Along the way, we'll delve into Ben's thoughts on best practices in data science, how the field is evolving and how we can all help to shape the future of this emerging discipline.
Jan 17, 2018
#3 How Data Science and Machine Learning are Shaping Digital Advertising
Claudia Perlich, Chief Scientist at DStillery, a role in which she designs, develops, analyzes and optimizes the machine learning algorithms that drive digital advertising, speaks with Hugo about the role of data science in the online advertising world, the predictability of humans, how her team builds real time bidding algorithms and detects bots online, along with the ethical implications of all of these evolving concepts.
Jan 17, 2018
#2 How Data Science is Impacting Telecommunications Networks
Chris Volinsky, AT&T Labs' Assistant Vice President for Big Data Research and a member of the team that won the $1M Netflix Prize, an open competition for improving Netflix' online recommendation system, speaks with Hugo. We'll be discussing the role data science plays in the modern telecommunications network landscape, how it helps a company that services over 140 million customers and what statistical and data scientific techniques his team uses to work with such large amounts of data. Along the way, we'll dive into the need for more transparency concerning the use of civilian data and Chris's work on the Netflix recommendation system prize.
Jan 17, 2018
#1 Data Science, Past, Present and Future
Hilary Mason talks about the past, present, and future of data science with Hugo. Hilary is the VP of Research at Cloudera Fast Forward, a machine intelligence research company, and the data scientist in residence at Accel. If you want to hear about where data science has come from, where it is now, and the direction it's heading, you've come to the right place. Along the way, we'll delve into the ethics of machine learning, the challenges of AI, automation and the roles of humanity and empathy in data science.
Jan 16, 2018
#0 Introducing DataFramed
We are super pumped to be launching a weekly data science podcast called DataFramed, in which Hugo Bowne-Anderson, a data scientist and educator at DataCamp, speaks with industry experts about what data science is, what it’s capable of, what it looks like in practice and the direction it is heading over the next decade and into the future. Check out this snippet for a sneak preview!
Jan 15, 2018