Raw conversations with practitioners from the worlds of artificial intelligence, machine learning, statistics, and data science.
- (2:05) Mark revisited his brief stint during college back in the 90s.
- (3:38) Mark’s first job as a Business Consultant at Dixon Stores Group was a humbling experience.
- (5:41) Mark stressed the importance of customer empathy that lasts with him throughout his career.
- (6:45) Mark talked about his next long-term job as a Configuration & Support Engineer at Orange PCS, where he built solid technical skills in IT and data work.
- (12:51) Mark discussed his next gig working as a Principal Specialist at T-Systems and then doing freelance work in IT and data analytics.
- (16:23) Mark reflected on the sabbatical years he took a break from working.
- (19:10) Mark shared an overview about his current employer, Mango Solutions.
- (20:34) Mark discussed his first big project working at Mango as a senior IT consultant.
- (25:57) Mark then transitioned into a technical architect role, where he became the bridge between the data science and the IT worlds.
- (28:33) In reference to his talk “An operating model for R”, Mark stressed the importance of policy, procedure, people and policing to build an effective operating model that connects data scientists and IT specialists.
- (34:32) Mark gave a client use case that his Data Engineering team has been involved with at Mango.
- (36:48) Mark talked about the cultural challenges of deploying code into production within an organization.
- (39:35) Mark talked about his key accomplishments in his leadership role as Head of Data Engineering.
- (43:27) In reference to his talk “R is production safe”, Mark discussed the existing challenges in the R-community to write production code.
- (50:39) In reference to his book “Field Guide to the R Ecosystem”, Mark shared the key developments in the R ecosystem in 2019 that he’s most excited about.
- (53:27) Mark gave thoughts on the rise of cloud-based processing technologies for data engineering’s best practices.
- (56:42) Mark mentioned the Google Cloud Certified Data Engineer Exam that people can take to learn about data engineering.
- (59:35) Mark emphasized the importance of communication skills to become an organizational leader.
- (01:01:13) Mark shared his view on the data science ecosystem in the UK.
- (01:02:18) Closing segments.
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Chintan is a data scientist currently working as advanced analytics manager at Avanade. He did his Ph.D. in Underwater Communication where he developed communication systems for commercial applications. He has over 10 years of R&D experience and has worked in academia, oil & gas and consultancy. He is passionate about data science and delivering projects that help companies derive actionable insights.
Thomas is a bioinformatician, turned software engineer, who enjoys developing tools for data scientists. His main interests are in the tools that bring the scientist closer to their data, whether it be through intuitive and powerful APIs or through visualization. He describes himself as a creative spirit who enjoys photography as well as generative art and graphic design, and he tends to try and combine this with his interest in programming whenever possible. Thomas lives just north of Copenhagen with his wife and two kids.
Ewan has been working professionally with numbers and computers for the past 13 years. During the past 6 years at Skyscanner, he has seen the data team grow from 2 analysts based in Edinburgh to a global team of 25+ data scientists making a global impact.
Christopher Peters is a full-stack data scientist at Zapier. He was both Zapier and Treehouse's first data scientist. Prior to his work as a data scientist, he was a research associate at LSU’s Center for Energy Studies where he was an energy economist. He has a real passion for working with, sharing, visualizing and analyzing data of all kinds using statistical, visual and machine learning techniques.
Saurabh Bhatnagar is the ex-Principal Data Scientist at Rent The Runway. He created the big-data analytics and recommendation platforms at RTR and scaled it to 30m users. RTR is now valued at $800m.
He was involved in many personalization incentives as well as back-end fulfillment algorithms that power the business. He also pioneered AI products at RTR like image search and recommendations.
Prior to RTR, Saurabh was founding member of the Quantitative Analyst team at Barnes & Nobles and helped it grow. His responsibilities at B&N were customer segmentation and propensity to buy models. Since 2000, he has consulted in data space for many Fortune 500 firms.
More recently, he founded Virevol, a retail AI startup.
Leni Krsová is social media data analyst from the Czech Republic, currently based in Prague. At the beginning of her career, she worked for Czech TV, a public broadcaster in the country, as a social media editor but switched quickly from marketing to the path of data analyst. Since then she is interested more and more in data analysis of social media and online news media data with R, data privacy and academic research in these fields. She is planning to start her PhD studies in near future.
Deep Narain Singh is Data Scientist with specialization in machine learning and deep learning. He has extensive work experience in building NLP/Computer Vision products using AI/ML/DL. He has spent 12 years in industry working with startups and large scale companies. He holds a Master’s degree in Data Science from University Of New Haven/Galvanize and completed his undergraduate in Civil Engineering from NIT Jaipur.
Dr. Jonathan Leslie obtained his Ph.D. in Biology from the University of London, studying blood vessel formation at the Cancer Research UK London Research Institute. After 20 years of researching the molecular processes underlying cancer, he turned to data science and founded a freelance consultancy business. He is passionate about promoting open-source software and routinely volunteers as a mentor in the R-programming and data science communities.