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9:00 AM - 5:00 PM

Data Science Festival MainStage Day

9:00 am-
5:00 pm
April 21st , 2018, Saturday

Data Science Festival Mainstage (Ballot ticket only)

CodeNode – 10 South Pl, London EC2M 7EB


Get Tickets

Due to the popularity of Data Science Festival events, we are now allocating event tickets via a random ballot. Registering here enters you into the ticket ballot for the Data Science Festival Mainstage day on Saturday 21st April 2018, the ballot will be drawn by the 17th April 2018. Those randomly selected will then be e-mailed tickets for the event, with the joining details.

Please note if you are attending any of our paid workshops on Friday, April 20th, 2018 you will automatically be sent a ticket to this MainStage event on April 10th 2018.

Please bring a copy of your paper ticket or your ticket on your phone to the event to check in with your QR code. Tickets are non-transferable.

The Data Science Festival is the first of its kind as the only community-led, free to attend Data Science Festival in the UK.

This free day will feature three-stream rooms with over 500 people attending. A day of lectures, tutorials and workshops with over 40 top speakers. It will also feature our partners in our exhibitor section of the event. An entire day to learn, mingle and be inspired. For the people by the people!

Speakers to date, please check for up to date speaker information.

Adam Hornsby – Dunnhumby

Ankur Modi – Status Today

Ed Klinger – Flock

Florian Doutteau – Dataiku

Gianluca Campanella – Microsoft

Jeremy Tarling – BBC

Jerome Le Luel – Funding Circle

Kasia Kulma – Aviva

Kayne Putman – SAS

Kostas Perifanos – Argos

Ling Zhang –

Magda Piatkowska – BBC

Marios Michailidis –

Michael Todd – Deliveroo

Phil Howard – King

Raoul-Gabriel Urma – Cambridge Spark

Scott Soutter – IBM

Soledad Galli – Data Science Coach

Sophie Sparkes

Tom Mack – Qubole

Will Moy – Full Fact


Adam Hornsby
Talk Abstract: Neural network embeddings are often used in Natural Language Processing (NLP) to model words and sentences. The unsupervised “2vec” algorithms (e.g. word2vec) learn embeddings extremely quickly, scale well and can create beautiful visualisations. dunnhumby have recently extended these algorithms to work with grocery retail data; helping us to…
Ankur Modi
Status Today
Talk Abstract: Can Artificial Intelligence be used to understand the intricacies of human behaviour? Ankur Modi shows how basic data and AI have the potential to bring the next revolution in employee engagement. The talk focuses on case studies where StatusToday’s technology was deployed with direct application to understand employee…
David Loughlan
Data Idols
Talk Abstract: David is the founder of Data Idols and the Data Science Festival.  He has spent years as a contract database administrator, delivering projects for some of the UK's leading companies.  During his time as a contractor, much of his work was sourced through recruitment agencies, it was a…
Ed Klinger and Courtenay Mansel
Talk Abstract: Real-time data for real-time insurance: a flying robot case study with Flock. Flock is a London based ‘insurtech' startup bringing drone insurance into the 21st century. Flock aggregates and analyses geospatial data in real time to identify, assess, and quantify the risk of a drone flight at the point…
Florian Doutteau
Talk Abstract: Artificial intelligence and machine learning are buzzwords that have entered the vernacular at many enterprises. And while some have been preoccupied with how AI will transform the way we work, few have managed to realize the full benefits of these technologies. For many, the question is man vs.…
Gianluca Campanella
Talk Abstract: Lessons learned from teaching Data Science. The current shortage of talent in Data Science has led to the creation of a plethora of courses and workshops, both online and in-person — but are we reaching the right audience, and giving them the right skills to close the talent gap? Starting…
Jeremy Tarling
Talk Title: The joy and pain of building multilingual recommendation system at the BBC News. Bio: Jeremy is an engineering manager with a background in data and systems architecture. Before the BBC he worked for a start-up called Simulacra that built graph-based metadata systems for public sector clients, a technology that he…
Jerome Le Luel
Funding Circle
Talk Abstract: Reinventing a traditional business through smart use of data science. Lending to small businesses has historically been a task banks have struggled with due to its complexity. Harnessing the latest data sources, technologies and analytical techniques, Funding Circle is succeeding at making the process of lending to small businesses…
Kasia Kulma
Talk Abstract: There’s a trade-off between complexity and interpretability of Machine Learning algorithms. This may pose challenges in building trust in those models, but also affect our society as a whole. Kasia will talk about current ways of evaluating those opaque (‘black-box’) models and their caveats. Then, she’ll introduce Local…
Kayne Putman
Talk Abstract: How do data scientists accelerate their analytics journey from statistics to machine learning to AI. SAS is the market leading machine learning and data science platform provider. In this session, we will highlight how the analytics landscape has evolved over the last 20 years and how SAS is continuing…
Kostas Perifanos
Talk Abstract: Word embeddings: Beyond word2vec. Word embeddings is a very convenient and efficient way to extract semantic information from large collections of textual or textual-like data. We discuss a comparison of the performance of  embeddings techniques like word2vec and GloVe as well as fastText and StarSpace in NLP related problems such…
Ling Zhang
Talk Abstract:  Building a Fast Fuzzy Searcher and Spell Checker. Spelling is hard, really hard. It's a an everyday user frustration to try to search for a friend's name or the name of a restaurant that they heard but end up writing it wrong. In this talk, we cover how to…
Magda Piatkowska
Talk title: The joy and pain of building multilingual recommendation system at the BBC News. Bio: Magda left academia as a systems engineer and computer scientist. She spent her first years of a career in Dublin building data infrastructure in a Telco company. Then moved to gaming industry to join Silicon…
Marios Michailidis
Talk Abstract: H2O’s Driverless AI – An AI that creates AI! Through my kaggle journey to the top spot, I have noticed that many of the things I do to perform competitively in data challenges can be automated. In fact automation is critical to achieve very predictive scores because while the…
Michael Todd
Talk Abstract: How to create business impact with Data Science. Machine learning and AI have transformed Deliveroo. Surprisingly, we find that this was achieved not by the latest theory or libraries, but from rigorous application of the principles of basic research: experimentation, incrementalism, and a bias to simplicity. In this talk,…
Phil Howard
Talk Abstract: How data helps keep King's players happily crushing candy, 5 years since launch. The Candy Crush franchise grew revenues over 2017, while Candy Crush Saga passed its 5th birthday. What keeps players coming back to enjoy King’s games for many years? I’ll share few of the ways that data science helps…
Raoul-Gabriel Urma
Cambridge Spark
Workshop Abstract: This workshop will provide a hands-on introduction to the Big Data ecosystem, Hadoop and Apache Spark in practice. Through practical activities in Python, you will learn how to apply Apache Spark on a range of datasets to process and analyse data at scale. After taking this workshop you…
Scott Soutter
Talk Abstract: Deep Learning gets Bigger: Larger Models, Better Distribution, and an end-to-end workflow for data science. What's changing in machine learning and deep learning? The increasing need for larger models and memory to handle high definition video, large data sets, and complex models. Open sourced large model support, accelerated machine…
Soledad Galli
Data Science Coach
Talk Abstract: Feature Engineering for Machine Learning. Machine Learning algorithms can determine patterns in past data and use them to predict behaviour in future data. To this end, machine learning models learn from existing data. However, available data in business is generally not ready for use in machine learning modelling. Instead,…
Sophie Sparkes
Workshop Abstract: Humans are visual creatures. Visualising data makes it easier for us to explore it, find insights, and helps people understand those insights to make decisions. In this hands-on workshop learn how to to visually analyse your data to find insights, then quickly turn those insights engaging and compelling,…
Tom Ewing
Department for Transport
Talk abstract: The Data Science journey in DfT, including initiatives, projects and our vision for the future. Bio: Tom Ewing is Principal Data Scientist for DfT. He has 20 years’ experience in government in a variety of data, analytical and digital roles and currently relishing the challenge of kickstarting the DfT’s…
Tom Mack
Talk Abstract: Big Data Activation. This session will discuss the gap that enterprises face today when activating their big data. It will uncover cover key trends and observations from Qubole's big data activation platform. This insight will present various ways that enterprises can measure their own activation readiness, and demonstrate the…
Will Moy
Full Fact
Talk Abstract: Automated Factcheckin. Factchecking is one solution to the multifaceted problems behind the catchall term 'fake news'. Join Full Fact, the UK's independent factchecking charity, to discuss how they plan to make factchecking dramatically more effective with technology that exists now, both here in the UK and beyond. Bio: Will has…