PyData Bristol – 24th Meetup

15 Jun 2023, 6:00pm - 8:30pm

Join us once again for the next PyData Bristol Meetup!
The PyData community in Bristol continues to thrive with engaging talks, insightful lightning sessions, and lively networking. A massive thank you to our generous hosts, Cookpad, for supplying the venue, Adlib for the scrumptious pizza, and thirst-quenching refreshments, along with additional sponsorship.

Agenda for the evening:
🚪 6:00 pm – Doors open
🕡 6:30 pm – Talks commence (sharp!)

📚 Two 25-minute talks:

  • Talk 1: Hiring for diversity – Dr Elena Hensinger-Schien
  • Talk 2: DBT – Data Build Tools – James Yarrow

📚 One 5-minute lightning talks:

  • Lightning Talk 1: Signal Processing with CNN – Michael Roberts
  • Managing a million tiles to (sort of) cure cancer – James Leech

📢 Community announcements
🤝 Relaxed networking over beers and soft drinks

Interested in sharing your knowledge or experience at this or a future event? Fill out this form to submit your talk proposal:
We look forward to seeing you there for another fantastic evening of Python, Data Science, and camaraderie!


1. Introduction to DBT – James Yarrow

DBT or Data Build Tools is a python library with a huge open source community and so much more. DBT focuses on the Transformation in ELT and is used by analytics engineers, data engineers and data scientist. It can be used to managed models in SQL server with great python extensibility and governance features.

2. Inviting diversity when hiring for data jobs – Dr Elena Hensinger-Schien

When looking to build a diverse team, the job description, the interview task and the overall communication experience can be either inviting or off-putting for candidates. This talk will share some best practice, such as inclusive language and a critical assessment of our interview goal and approach, that will be beneficial not only to candidates from underrepresented groups within data, but all candidates.

Lightning Talks

# 1. Signal Processing with CNN – Michael Roberts

This talk will give a brief overview of a method to apply Convolutional Neural Networks to analysis of audio data through the use of the Discrete Fourier Transform. This approach is used in the current state-of-the-art algorithm for musical segment boundary detection, the subject of my MSc thesis.

# 2. Managing a million tiles to (sort of) cure cancer – James Leech

Medical computer vision is complicated because biopsy scans are huge. Think of it as a satellite map analysis tool, where you are trying to read the road marking to determine what country you’re in. It’s a subclass of image analysis called multiple instance learning. In this lightning talk I want to introduce the specific challenges associated with medical computer vision, some solutions I’ve learned thus far, and some gaps in current technology you could fill to make yourself rich.

Talks kick off at 18:30 sharp; then networking in The Knights Templar from 20:40.
If you realise you can’t make it, please un-RSVP in good time to free up your place for your fellow community members.
Follow @pydatabristol ( for updates on this and future events, as well as news from the global PyData community.

The PyData Code of Conduct governs this meetup ( To discuss any issues or concerns relating to the code of conduct or behaviour of anyone at the PyData meetup, please contact the PyData Bristol organisers, or you can submit a report of any potential Code of Conduct violation directly to NumFOCUS (


Dr Elena Hensinger-Schien, James Yarrow, James Leech, Michael Roberts

Dr Elena Hensinger-Schien on Inviting diversity when hiring for data jobs

Mike has been working in academic publishing for over 16 years. His data science journey started over ten years ago, using natural language processing to semantically enrich documents. More recently he has worked on projects to forecast user web behaviour, provide custom content recommendation systems, and generate long-range customer churn predictions. He has an MSc in Data Science from University of the West of England.

James Leech is Machine Learning Engineer at Sonrai Analytics, where I am developing computer vision algorithms to replace slow and expensive “wet” lab tests for cancer screening with a faster and cheaper image analysis of biopsy scans. 

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