PyDataMCR October

PyDataMCR October

THE TALKS

The Data Architecture behind John Lewis Partnership's Return to Profit - Anna Aleshko (She/Her) and Jacopo Coluccino (He/Him)

In this presentation, Jacopo and Anna will take you through the data journey of the John Lewis Partnership, exploring the evolution that led to the creation of the Partnership Data Platform (PDP). We'll delve into the history, the challenges we faced, and the strategic decisions that brought us to where we are today. Additionally, we'll share a real-world example of how PDP teams are able to deploy production ready data pipelines with external third party integrations in a matter of days.

Anna Aleshko is a Data Engineer at John Lewis Partnership where she is part of the Waitrose Online team. With an educational background in biochemistry & experience spanning several industries, she brings a unique perspective to her work. As Founder & Co-Organizer of Data Engineers London, she is passionate about knowledge sharing & community engagement among data professionals.

Jacopo is a Data Engineer at the John Lewis Partnership and a Software Engineering Master's student at the University of Oxford. In his current role, he leads the Partnership's Customer Data team, where he is instrumental in establishing a robust customer data infrastructure on the new Snowflake platform. With a passion for crafting Python solutions grounded in solid object-oriented design, Jacopo excels at integrating business insights with data-driven decision-making.

Revamping our A/B testing methodology - everything is a histogram if you squint! - Dustin Hayden (He/Him), Tom Armitage (He/Him)

Auto Trader is always striving to improve the user experience on the website, constantly making changes. Understanding the impact of these changes is vital to know if our changes are having the intended effect. A/B tests are the go-to quantitative gold standard, but there are many different methodologies to choose from when it comes to analysing the data. In this talk, Dustin and Tom will discuss Auto Trader’s shift to a Bayesian framework, the benefits of this, the challenges, and how they developed approaches to overcome them.

Tom is a data scientist at Auto Trader with a background in computational astrophysics, where he first developed an interest in ML. He has worked on various products involving imagery, forecasting, and optimisation, with his current projects focusing on search and recommendation systems.

Dustin is a data scientist at Auto Trader with a background in neuroscience. He is currently developing models for search at Auto Trader and models for polyphonic note detection at home.

Location
We'll be at AutoTrader, who are kindly supplying the venue and catering. The capacity is limited to 80.

EVENT GUIDELINES

PyDataMCR is a strictly professional event, as such professional behaviour is expected.

PyDataMCR is a chapter of PyData, an educational program of NumFOCUS and thus abides by the NumFOCUS Code of Conduct

https://pydata.org/code-of-conduct.html

Please take a moment to familiarise yourself with its contents.

ACCESSIBILITY

Under 16s welcome with a responsible guardian. There is a quiet room available if needed. Toilets and venue are accessible.

SPONSORS

Thank you to NUMFocus for sponsoring Meetup and further support.

Thank you to AutoTrader for their sponsorship and for the awesome venue and catering!

Thank you to Krakenflex for sponsoring PyDataMCR.

Thank you to John Lewis for sponsoring this PyDataMCR event.