Data Futurology - Data Science, Machine Learning & Artificial Intelligence From Top Industry Leaders
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
Sally is the General Manager of Insights at the Australian Motoring Services. She previously spent 10 years working in banking and today she shares her story. We speak about: * Fraud analytics in big banks * End to end analytics * Importance of fast feedback loops * Shocks of early working life * Balancing speed & accuracy * 80/20 vs 95/5 * Exposures in strategy & politics * Helping the business ask the right questions * Leading with the work * Career breaks: how to * Importance of working on yourself * Advantages of medium sized companies * Creating a data strategy * Balancing tactical solutions, strategic initiatives and team development * Self service analytics * Educating business stakeholders & getting their feedback * Ability to ask anything from everyone * Data science is like medicine * Leveraging multiple dimensions for career development * Knowledge sharing sessions * Getting analytics a seat at the table Show notes: www.datafuturology.com/podcast/34 Sally 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!
Graeme started in actuarial science and developed a love for algorithms and automation. He worked in data warehousing before moving into data analytics. He spent 16 years in several Head of Data roles at The Automobile Association (AA) before joining Addison Lee as their Chief Data Officer, where he is today. We speak about: * What is actuarial science * Data warehousing & GIS systems * Overview of the Chief Data Officer role * Automation in the data space * How to build a data warehouse * The difference between a data warehouse, data lake and virtual data warehouse * Starting data work with business problems/questions * How to deliver value to the business * Balancing tactical project delivery with strategic work * Enabling self service data analytics * Prioritising & sizing up work * Modern styles of work in data * Data governance: creating a plan * Creating a data strategy * How to get to a head of role * Team building * Networking Show notes: www.datafuturology.com/podcast/33 Graeme is based in London, Greater London, United Kingdom 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!
Carole had an unusual path into data science. She's worked as a content project manager, in strategic planning and in sales before getting into data through Business Intelligence at Fyber where she eventually became their Head of Analytics. Today she is the Head of Data Science & Analytics at Tenjin. We speak about: * The strengths of being a generalist * Upskilling throughout your career * Focus on self service reporting * The skills needed in a BI team * Creating internal user groups to share knowledge * Convincing people to get training on the tools required to do their job better * The benefits of gaining a reputation internally * Setting a strategy for data teams * The importance of data modelling skills in data teams * Learning technology on the job when you're background is not technology * Monthly meeting with key departments to review all dashboards in the department * Working remotely in global companies * Metrics about user behaviour * Offering analytics for many customers with the same problem/need * How to develop consulting skills * The platinum rule - book on communication style * The leadership challenge - book recommendation * What it's like working in startups * How to recover from being a workaholic Show notes: www.datafuturology.com/podcast/32 Carole is based in Berlin Area, Germany 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!
Scott started his career pushing trolleys at Woolworths. In his career he rose to management levels in retail with Woolworths, consumer goods with Kraft Foods, Fonterra SPC and PZ Cussons, then in media with 21st Century Fox. He then became the CEO of iSelect, a role he left earlier this year to start his own AI company Wilson AI. We speak about: * Focus on customer needs * Digitising industries to access more data * Helping companies in multiple industries to begin their data analytics journey * How to differentiate your company when competitors have access to the same data * How to overcome being "data rich but insight poor" * Changing industry power dynamics through data * Creating new teams to create value from data * The importance of storytelling in data science * Defining objectives with your data analytics communication * Educating industries to use data more effectively * Understanding costs & priorities across the value chain to make better decisions * Eliminating your biases when dealing with customers * Process re-engineering & AI * How to think outside of the building * How to start an AI company * The importance of translating between business and technical * How to connect data science and the boardroom * The importance of data science education in an organisations journey * How to achieve a wider spread adoption of AI * Focusing on cost & revenue with data science for maximum impact * Resist the urge to boil the ocean * The role of a CEO in a publicly listed company * Focusing on the top 3 business priorities * Productionising AI & monitoring unintended consequences Show notes: www.datafuturology.com/podcast/31 Scott is based in Sandringham, Victoria, 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!
Aaron started his career working in accounting and building management information systems (MIS). He had his own company, worked in multiple industries and then got into biology and genomics. Today he is the Chief Data Officer at the Inova Translational Medicine Institute. We speak about: * How to take research into scaled applications * The importance of sharing your knowledge and helping others understand * Why you're only as good as your team members * How to engage many different types of stakeholders * Challenges of data management in healthcare * Data governance & provenance in healthcare * Data monetization & it's stigma in healthcare * The benefits of data sharing consortiums * The potential of genomic & DNA data * Handling algorithm biases * Enabling reproducible research through data * Why "perfection is the enemy of good" * The importance of creating & sharing your mental models Show notes: www.datafuturology.com/podcast/30 Resources: Weapons of Math Destruction https://weaponsofmathdestructionbook.com Evernote https://evernote.com Real time board https://realtimeboard.com Mind jet - mind mapping https://www.mindjet.com Aaron is based in Washington DC Metro Area, USA 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!
Klaus started his career doing internships at Yahoo! and the port of Hamburg. He worked as a consultant and completed a PhD in Quantitative Marketing. Today he is the Chief Analytics Officer at YAS.life We speak about: * The importance of getting applied experience as early as possible * Defining KPIs for businesses * Using data to change organisational behaviour and increase safety * How to navigate organisations to create data definitions * Realities of consulting: positives and negatives * Why large companies require so much custom work * How to help people and organisations that don't know what they want * Helping organisations in progressing through their analytics journey * How to overcome technical challenges with creative solutions in your projects * Why honesty within yourself and others is imperative in your work * How to provide customers what they need instead of what they want * The importance of hard and soft metrics when measuring value * Applying soft skills in data science * How to find what will be valuable for your customers * Expanding your interest with a postgraduate degree * How your social surroundings affect your purchase decisions * Using soft skills for data acquisition * What is eigenvector centrality and what is it used for? * How product reviews influence your buying decisions * How to create experiments in business * Pricing models in the steel business * Data science in fitness startups Show notes: www.datafuturology.com/podcast/29 Klaus is based in the Berlin Area, Germany. 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!
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