About us
Come for the content, stay for the community!
Live Festivals - In-Person Meetup’s - Online Events
The DSF, founded in 2016, is a diverse community that prides itself on its free knowledge sharing, educational events and festival vibes. Sharing our knowledge of tech from an open source perspective is the only way we can really evolve our bigger ideas. To inspire people to use data for good and connect the community and companies together to better humanity.
Find out more at datasciencefestival.com
Upcoming events
2
Building Data at Scale: Engineering for Speed, Reliability and Accuracy
Location not specified yetWelcome to DSF Sandbox Sessions!
Top tech talks and masterclasses from the best in the industry. Every month, and completely free. The catch? There isn’t one. Just a monthly dose of epic content to power up your data passion!
Event details
📆 Date: Wednesday 4th November 2026
⏰ Time: 6:00 – 9:00 PM GMT
💡 Topic: Building Data at Scale: Engineering for Speed, Reliability and Accuracy
🗣️ Speakers: Tim Renton, Antonio Alvarez Caballero, Matt Bailey, Yijie Hsieh and Yong RenHow do you build a data platform that delivers pricing decisions in under a minute, supports machine learning models and still provides accurate, auditable data for financial reporting?
Join Data Science Festival and tem at Battersea Power Station for an evening exploring the real-world engineering challenges behind building and scaling a modern data platform.
We'll hear how tem's data function has evolved from Google Sheets to a modern technology stack featuring ClickHouse, dbt, Omni and AWS, including the technical decisions, challenges and lessons learned along the way.
The evening will feature a keynote from tem's Head of Data, a panel discussion bringing together practitioners from across data engineering, analytics and machine learning,
and plenty of opportunities to network over food and drinks.Check out the full session details below!
KEYNOTE SESSION
From Google Sheets to Sub-Minute Pricing: Lessons in Scaling a Data Platform
Speaker: Tim Renton, Head of Data @ temWhen you're building the data function at a growing technology company, how do you know which foundations to invest in, which shortcuts are worth taking and when it's time to rethink your approach?
At tem, the data platform has evolved from Google Sheets to a modern stack supporting complex energy transactions, with pricing decisions delivered in under a minute.
In this session, Tim Renton shares the journey of building and scaling tem's data function, exploring the architectural decisions, technical challenges and lessons learned along the way.
Discover how the team's approach to data engineering, analytics and infrastructure has evolved as the business has grown, the trade-offs involved in balancing speed with reliability, and what Tim would do differently if he were starting again.
PANEL SESSION
Speed vs Accuracy: The Hidden Trade Offs of Modern Data EngineeringWhat happens when the same data needs to support real-time decisions, financial reporting, machine learning and regulatory compliance, all with different expectations around speed, accuracy and reliability?
At tem, these aren't hypothetical challenges. The data platform supports energy pricing decisions in under a minute while also providing consistent, reconciled and auditable information across the wider business.
Bringing together practitioners from across data engineering, machine learning and analytics, this panel explores the technical and organisational challenges of building a shared data platform that works for everyone.
We'll explore questions including:
- How do you balance low-latency requirements with data quality and accuracy?
- Where should responsibility for data quality, definitions and ownership sit?
- How do you design a platform that supports both operational decisions and financial reporting?
- What happens when different teams have conflicting requirements?
- How do data engineering, analytics engineering and machine learning teams work together to solve these problems?
Expect a practical discussion about the trade-offs, architectural choices and collaboration required to build trustworthy data systems at scale, with lessons relevant well beyond the energy industry.
Panellists:
Antonio Alvarez Caballero – Staff Data Engineer @ tem
Matt Bailey – Senior Machine Learning Engineer @ tem
Yijie Hsieh – Staff Analytics Engineer @ tem
Yong Ren – Staff Data Analyst @ tem
Hosted by: David Loughlan, Founder
@ Data Science Festival and Data IdolsEVENING SCHEDULE
6:00 PM – Doors open, food, drinks and networking
6:45 PM – Welcome from Data Science Festival
6:50 PM – Keynote session
7:20 PM – Short break
7:30 PM – Panel discussion
8:10 PM – Drinks and networking
9:00 PM – Event closeABOUT TEM
tem is building new transactions infrastructure for a modern energy market, with the aim of making access to lower-cost electricity simpler and more transparent.Using AI and technology, tem is rethinking how businesses and generators transact energy. Today, its RED platform powers more than 6,000 UK customers, with a focus on creating a more transparent energy market.
Find out more about tem: tem.energy
TICKETING INFORMATION
Please note: Due to expected demand and limited capacity, this event will be run as a ballot. The exact venue location will be shared with successful applicants when tickets are issued.
Applying for the event does not guarantee a ticket. Applications will be reviewed on a rolling basis. If you have not received a ticket by Thursday 29th October, unfortunately your application has not been successful.
Please note that adding the event to your calendar does not confirm your place. Your place is only confirmed once you receive your ticket by email.
You can find out more about how our ballot works in the DSF Ticketing 101.
HOW TO REGISTER
To apply for a ticket, click the registration link below and complete the ticket ballot form.
Successful applicants will receive their tickets via email, along with further details about the event location.PLEASE NOTE: Clicking 'attend' on Meetup does not register you for the event. You must enter the ticket ballot using the link below to be considered for a place.
CLICK HERE TO ENTER THE TICKET BALLOT!
Please note the time zone when booking this event.
1 attendee
Online event: Zooming in on a Forecast
·OnlineOnlineWelcome to DSF Sandbox Sessions!
Top tech talks and masterclasses from the best in the industry. Every month, and completely free. The catch? There isn’t one. Just a monthly dose of epic content to power up your data passion!
⭐️ Zooming in on a Forecast
📆 Thursday 26th November 2026
⏰ 1:00 pm - 2:00 pm GMT
💻 Online webinar🎟️ CLICK HERE TO REGISTER FOR FREE! 🎟️
💡 About the event:
Join us online on Thursday 26th November for our next session with dunnhumby, featuring Marco Brambilla, Research Data Science Specialist, as he explores how data scientists can add greater detail to forecasts without rebuilding forecasting systems from scratch.
In retail analytics, forecasts are produced at scale. Senior stakeholders often want them broken down further by shopper type, demographic group, or other business dimensions. How can data scientists provide this extra detail? Should they build more granular models, rely on historical averages, or use a different approach?
Photography faces a similar challenge. Optical zooms capture genuine detail at a cost. Digital zooms are cheaper but lose detail. Modern AI-enhanced zooms can create sharper, more detailed images without more expensive hardware.
Can forecasting be approached in the same way?
In this session, we use the analogy of optical zooms, digital zooms, and AI-enhanced zooms to explore three approaches to adding detail to forecasts. You will leave with a practical framework for understanding when simple methods are sufficient, when additional modelling is needed, and how greater forecast detail can be achieved without rebuilding forecasting systems from scratch.
🎤 Speaker:
Marco Brambilla, Research Data Science Specialist @ dunnhumby
Research Data Science Specialist with 18 years’ experience at dunnhumby, designing and delivering scientific solutions that generate automated demand forecasts at scale for leading grocery retailers. For 10 of those years, I managed and developed data science teams while continuing to lead work on pricing, forecasting, and the measurement of intervention effects. My work has focused on the science and tools that support commercial decision-making and large-scale analytics capabilities.
I believe that strong scientific foundations are essential for building predictive modelling solutions that are both practical and scalable. A principled approach improves prediction accuracy and interpretability. It also makes solutions easier to extend, integrate, and operationalise while maintaining consistency across different applications.
My technical interests include mathematical modelling, statistical inference, and causal reasoning. I hold BSc and MSc degrees in Computer Science, specialising in Complex and Intelligent Systems. I subsequently completed a PhD and postdoctoral research in Computational Neuroscience.
🎟️ CLICK HERE TO REGISTER FOR FREE! 🎟️
Registering for the event: Click the ‘Register here’ button using the link provided. Once you have completed the registration form, you will receive an email containing your unique webinar joining link. You will also receive reminder emails one week, one day, and one hour before the event.
🚨 PLEASE NOTE: Clicking ‘Attend’ on Meetup does not register you for the event. You must register using the link below to receive your webinar joining link. Without a joining link, you will not be able to attend.
6 attendees
Past events
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