Summary: Data Futurology is data from a human lens. In Data Futurology, experienced Data Science Leaders from around the world tell us their stories, challenges and the lessons learned throughout their career. We also ask them: - What makes a great data scientist? What skills are required? - How to become a great data science leader? - How should I grow and get the most out of my team? - What is a good data strategy? and how do I best implement it? - What are interesting applications of ML/AI that I should be considering in my industry? To find out more visit www.datafuturology.com
Jennifer started her career as a particle physicist before becoming a data scientist. After gaining experience in many fields including high frequency algorithmic trading & advertising, she was Atlassian's first Chief Data Scientist. Today she is the VP of Machine Learning at Figure Eight and an Expert and Advisor at the International Institute for Analytics. We speak about: * How to see the results of your work sooner and faster * The importance of choosing your manager * Making data strategy decisions for companies that are very immature in their approach to data * Building data science teams from scratch * Combining impostor syndrome and leaps of faith for your benefit * The importance of making mistakes to be successful * What having a great data culture really means * How to convince peers and supervisors on the benefits and the path of data strategy * Differences between having a technical and non-technical manager * Combining technical abilities and business sense * The importance of customer contact for technical people * Focus on the impact and outcome of everything that you're building * How to keep the balance in teams * Pleasing customers vs product intuition * How to drive and create a data driven culture * How to create scale with your data science efforts * How to build your data science team * Data engineering vs Machine learning engineer * How to keep talent * How can data scientists learn the skills for business leadership * Active learning and building products for data scientists Show notes: www.datafuturology.com/podcast/28 Jennifer is based in Mountain View, California And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. It really helps new data scientists find us. Thank you so much, and enjoy the show!
Mark used to be a statistics lecturer at Nelson Mandela University in South Africa. He then joined First National Bank as a quantitative analyst where he climbed through the ranks to Head of Advanced Analytics and beyond. Today he is the Chief Analytics Officer at FNB. We speak about: * Predicting what the customer is calling about * Improving compliance in banking through analytics * Creating and driving a data strategy across an organisation * Using analytics to look after customers in better ways * How to create and measure economic value from data * How to find meaning in your work * Understanding your value across the entire value chain * Creating a culture of collaboration that's not afraid to fail * Working with tertiary institutions to identify talent * What to test when interviewing data scientists * How to structure your team & work with stakeholders * The importance of data governance * How to implement and socialise the solutions created by the team for maximum impact * The importance of mentoring and growing people * The difference between head of analytics and chief analytical officer Show notes: www.datafuturology.com/podcast/27 Mark is based in the Johannesburg Area, South Africa And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. It really helps new data scientists find us. Thank you so much, and enjoy the show!
Sam's background is in sports & exercise science. He has an accomplished career in sport analytics. Today, he is the Head of Research and Innovation at the Western Bulldogs and an Associate Professor at Victoria University. We speak about: * Using ML to help people see the non-linerarity in their problems * Common misconceptions of ML * Interpretability of ML * Using ML to improve athletes performance, measure their contribution & prevent injuries * Carving a data science job in an area you're interested in * How to choose projects to focus on * Mixing psychology, operations and data science in sport * Data collection & management in sport * How data can help off field & the mental side of the athletes * Similarities of data in sport and government/ corporate * How athletes change when fatigued * Applications of sports analytics * How data can help create drills to improve player performance & skills * Current modelling challenges in sport * Real time decision making in game by coaches: challenges and realities * Educating stakeholders Show notes: www.datafuturology.com/podcast/26 Sam is based in Melbourne, Australia And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. It really helps new data scientists find us. Thank you so much, and enjoy the show!
Ben started his career as a chemical engineer. He developed an interest for computer vision early on. He worked for Intel, then at a hedge fund and then became the Chief Data Scientist at HireVue. A couple of years ago he started his own AI startup called Ziff.ai where he's is building a Deep Learning platform for product visionaries and software engineers. We speak about: * How computers amplify us * What it looks like to start your own AI company * How to switch programming languages * Downsides of Google's tensorflow * What industry expects from data science * How to deliver value with ML * How to pick ML projects to tackle * Eliminating bias in AI applications * AI powered job interviews of the (near) future * Topic discovery with DL * AI warfare in business * What is a Hive Mind and how it works * Future health care assessments at home * AI is cute until it's scary * The importance of passion and obsession in data science Show notes: www.datafuturology.com/podcast/25a Articles by Ben on Linkedin: This is Why Your Data Scientist Sucks: https://www.linkedin.com/pulse/why-your-data-scientist-sucks-benjamin The Al War Machine: Our Darkest Day https://www.linkedin.com/pulse/ai-war-machine-our-darkest-day-ben-taylor-deeplearning-/ The Al War Machine: The Hive Mind https://www.linkedin.com/pulse/ai-war-machine-hive-mind-ben-taylor-deeplearning- Getting That Data Science Job https://www.linkedin.com/pulse/getting-data-science-job-ben-taylor-deeplearning-/ From 0 to $100K+ data science job in 6 months https://www.linkedin.com/pulse/from-0-100k-data-science-job-6-months-ben-taylor-ai-hacker/ Ben is based in the Provo, Utah Area And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. It really helps new data scientists find us. Thank you so much, and enjoy the show!
This is a different type of episode! This episode is a presentation I recently did at a large financial services institution. I presented on 5 Mistakes and Lessons Learned in Driving Business Value with Data Science and the Cloud. I talk about: - Using Lean Startup and Design Thinking principles in Data Science - The importance of staying close to your end customer and what that looks like in practice - The difference between machine learning for machines and for humans - What is the purpose of ML/AI and how you can bring that thinking into your organisation - What using ML for humans looks like - Using data from other areas - Leverage the flexibility of the cloud Show notes: www.datafuturology.com/podcast/24 Slides: http://bit.ly/df-5mistakes Felipe is based in Melbourne, Australia And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. It really helps new data scientists find us. Thank you so much, and enjoy the show!
Mario is an Electrical Engineer from Colombia. He went to Silicon Valley to do his Masters at Stanford University and stayed to build a career in Marketing Analytics. He has incredible experience and has worked at Intuit, Google, HP, Symantec and Facebook. He currently works at Uber as Marketing Analytics and Data Science Manager. We speak about: - Starting in marketing analytics without knowing anything about it - Data dictators and why multiple versions of the truth are necessary - The importance of data science education in organisations - How to pick the best predictive model for your applications - How to use people analytics - Google style - Why your job is to empower your stakeholders - How to stand out during interviews Show notes: www.datafuturology.com/podcast/23 Mario is based in the San Francisco Bay Area And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. It really helps new data scientists find us. Thank you so much, and enjoy the show!
Kshira has been with the Analytics/Decision Sciences industry for almost a decade now having worked across Americas, Asia, Europe and Australia. He is the Head of Analytics and Data Science at The Iconic. We speak about: -Why he moved from analytics consulting to building data products -What a data driven product should do and how to prioritise your efforts -How to make analytics less intimidating and more accessible -How to take your stakeholders on the data-driven decision making journey in next the best way -How to structure your team for maximum impact in your organisation -Most common issues and roadblocks in creating a data driven culture and how to overcome them Show notes: https://www.datafuturology.com/podcast/22 Data Scientist job https://github.com/theiconic/datascientist Kshira is based in Sydney, Australia And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. It really helps new data scientists find us. Thank you so much, and enjoy the show!
Antony stumbled into his love of predictive modelling at the tender age of 10. He started his professional career in biostatistics and then made the switch to corporate Australia to work as Head of Analytics in banking before joining Seek; where today he is the Director of Global Matching and Analytics. We speak about: - how analytical thinking adds value both in research and in corporates - why you should read an intro to epidemiology textbook - why this is the most exciting time to be in analytics - his transition from research to corporate - surprises and rewards of moving into corporate - how to use the constraints you have for your benefit - how to stand out in data science interviews and much, much more! Show notes: www.datafuturology.com/podcast/21 Antony is based in Melbourne, Australia And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. It really helps new data scientists find us. Thank you so much, and enjoy the show!
David studied applied physics and began his career as a consultant. He’s had his own company where he created a video asset management & workflow software in the 90s!. Then worked in the education/not-for-profit sector and then went into the finance sector as VP of BI & Data Analysis. Today, he is the Senior Vice President and Head of Data, Analytics and Research at BankMobile. We discuss: - the insights into large companies from his early days in consulting - why technology provides the “guard rails” for the business - why our roles as data scientists is to make sense of the mess - what’s missing in today’s analytics education and how to learn what you need - what to look for when building a diverse team - the importance of creating a narrative in analytics - the mindset to maintain during your analysis - motivations behind problems with data definitions - how data is like a flashlight Show notes: www.datafuturology.com/podcast/20 David is based in Providence , Rhode Island, USA
Vlad started his career in visual effects & computer graphics. He worked on Hollywood blockbusters such as Avatar, Dark Knight, Happy Feet. He currently is Head of Data Science at Wooga which makes June’s Journey (Facebook Game of the Year 2017), Pearl’s Perils, Diamond Dash and many more. We speak about: - why it’s important to follow your curiosity and what that looks like how to keep learning and stay current in data science - uses of pytorch, the second deep learning python library after tensorflow which is backed by facebook - relevant metrics & analytics in the gaming industry - statistical modelling, machine learning & deep learning in gaming - considerations for deploying ML models to production - the importance of speed in delivery of work & reproducibility of data science - how to keep innovating for your customers - what is the semi-embedded model and much, much more! Show notes: https://www.datafuturology.com/podcast/19 Vlad is based in Berlin, Germany
Ahmed started his career at Siemens research, worked in startups, at Google, PayPal, SAS and JPMorgan and has his own machine learning company and now he runs data science at Equinor We speak about: - benefits of simulations in research and data science how he went from “equation-driven” to “data-driven” - the role of simulations in optimisation, decision-making and automation - uses of simulations and deep reinforcement learning models in the energy industry - how data is used 2-5kms underground below the sea to infer the properties of the ground underneath - lessons from startups and what to look for in people to work with - why it’s important for data science teams to own the engagement of value creation with the customer - how to ensure that your data science team is creating value in your organisation - how to prioritise the work done by your data science team and what to aim for; and much much more! Show notes: www.datafuturology.com/podcast/18 Ahmed is based in London, UK
Naomi Clarke started as a graduate in the oil business, since then she's worked in multiple industries, and now she is Head of Data in the finance sector. Naomi has a strong background on business data arch, business data modelling, data governance. I loved the human-centred perspective that she has taken to her work. We talk about: - the Management Information Systems (MI or MIS) she created in her early days - the importance of business data models for analytics - the difference between a logical and physical data model and which one is more important - how to define the right meaning of the data in your data models - disruptions in the financial sector that happened overnight - the relationship between deregulation, dematerialisation and digitalisation; and how its affecting industries - the tight link between business, data and culture; and how each one affects the others and much, much more! Show notes: https://www.datafuturology.com/podcast/17 Naomi is based in London, UK
In this episode we speak with Apollo Gerolymbos who is the Head of Data Analytics at the London Fire Brigade. We speak about: - the applications of data science in firefighting - how the London Fire Brigade (LFB) uses data to preempt and minimise fires - the end to end data science process at the LFB - how their data affects laws, policies and citizens’ lives - how Natural Language Processing (NLP) and text analysis is used on the reports of the most serious fires to identify new patterns of high risk factors - the importance of identifying bottlenecks and weak points in the availability of your service - why it’s important for data scientists to educate non-data people in their organisations and much, much more! Show notes: https://www.datafuturology.com/podcast/16 Apollo is based in London, UK ------------------ Also, catch me at the Chief Data & Analytics Officer Conference in Melbourne on September 3-5, 2018 https://chiefdataanalyticsofficermelbourne.com
In this episode we speak with Tony Laing who is the General Manager of Analytics & Data Services at Auto & General. We talk about: - what is the ‘nuts and bolts’ of analytics - what is the data supply chain required in organisations for the delivery of analytics/ML solutions - how to deliver quick wins and strategic projects concurrently - the journey to add significant value in an organisation through analytics - what questions to ask executives to kickstart their data science journey - why is there so much turnover in data science - why data preparation and model building is only 20% of the job - what type of model is the best to drive commercial outcomes - whether ML applied in specific domains is AI or not - the art of data preparation, increases in computing power and automation of data science - what is “the knife fight” of data science and what type of companies can benefit the most Show notes: https://www.datafuturology.com/podcast/15 Tony is based in Brisbane, Australia
In this episode we speak with Dr Gabriel Maeztu who is the Co-Founder and & Chief Data Scientist at IOMED Medical Solutions. We talk about: - his background, how he went from medicine to data science and how he combines medicine, data science & entrepreneurship - how to start coding when everyone around you tell you you’re crazy - image processing in medicine, using scikit learn to classify patients - how to use data science to validate what you’re taught in medical school - economical Incentives of the medical system that is probably slowing down progress in the data space - GAFAs: Google Apple Facebook Amazon in medical data - value based care built on data science - NLP/text processing in medicine - current & future data challenges in medicine and much, much more! IOMED is hiring data scientists! https://angel.co/iomed/jobs/379740-data-scientist Show notes: https://www.datafuturology.com/podcast/14 Gabriel is based in Barcelona, Spain