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PyDataMCR May Talks

THE TALKS

How do you go from not fitting into tech, to using data and AI to drive real impact? - Elizabeth Osanyinro (she/her)

In this talk, I’ll share my journey from, Archaeology to digital marketing and finally the world of data science and machine learning. Along the way, I’ll walk through the actual tools and resources I used, the projects that helped me grow, and the biggest lessons I learnt.

But this is more than a career pivot story. It’s about what non-traditional backgrounds bring to technical spaces. It’s about how “outsiders” can shape more user-focused, ethical, and accessible AI, and it’s about why diverse thinking isn’t just nice to have, it’s necessary.

Elizabeth Osanyinro is a Business Analyst at CarbonNote AI, driven by a passion for AI ethics, fairness, and inclusive technology. Currently completing an MSc in Applied Artificial Intelligence and Data Analytics at the University of Bradford, she brings a unique perspective shaped by her early career in digital marketing.

Elizabeth transitioned from digital marketing into data and AI to pursue more impactful, data-driven problem-solving. Since then, she has contributed to a range of projects including sentiment analysis, retail analytics, credit card fraud detection, and blockchain-based digital verification. She is proficient in Microsoft Excel, Python, R, SAS, Power BI, and Looker.

As the organiser of PyData Bradford, Elizabeth actively promotes community-driven learning and encourages inclusive dialogue around the responsible use of AI and data science.

Platforms for valuable AI Products: Iteration, iteration, iteration - John Carney (he/him)

In data science experimentation is vital, the more we can experiment, the more we can learn.

However quick iteration isn't sufficient we also need to be able to easily promote these experiments to production to deliver value. This requires all the stability and reliability of any production system.

John will discuss building platforms that treat iteration as a first class consideration, the role of open source libraries, and balancing trade-offs.

LOCATION We'll be at Krakenflex, who are also kindly supplying catering. The capacity is limited to 90.

After the talks we'll all head somewhere local for some post-event socialising.

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 are accessible.

SPONSORS Thank you to NUMFocus for sponsoring Meetup and further support Thank you to AutoTrader for sponsoring PyDataMCR. Thank you to Krakenflex for sponsoring PyDataMCR, as well as hosting this event!

PyDataMCR May!

THE TALKS

Using data science to get personal health insights from smart wearables - Richie (Thomas Manandhar-Richardson) (he/him)

In recent years there has been a boom in smart wearables for tracking sleep, stress, and exercise. Millions are now wearing a variety of devices from Apple Watches, FitBits, to Whoop Bands and Oura Rings. While they all offer in-app ways to explore your personal health data, data-savvy users can dig deeper using their APIs. Using 2 years of my own sleep and activity data collected from my Oura ring, we'll delve into what these devices can teach us about our health. I'll share practical tips on data collection, the statistical methods you can use to maximise your insight, and the surprising difficulties you might encounter when AB testing ways to improve your sleep.

Richie is a data scientist at both Peak AI and Bryant Research. At Peak, he builds AI applications for leading companies, primarily in retail, with a focus on understanding customer behaviour and using AI to optimise prices. At Bryant Research he uses his data skills to conduct research on how to build a food system that is better for people, the planet, the economy, and animals. His main areas of interest are in causal inference and AB testing, Large Language Models as well as data for good. Outside of work he enjoys vegan junk food, borrowing other people's dogs, Latin dancing and Obsidian.md.

Has Python found its Mojo? A New language for ML and AI - Joe Mulvey

Mojo is a new language designed to be a superfast superset of Python - a sort of Python++. It is intended to make Python's ease of use and accessibility available to people who need fast execution - especially those working in ML and AI. It has been hyped as "the biggest programming advance in decades". Does it live up to its billing?

Joe is head of Data Engineering at Northcoders. After a career in finance (mainly with Barclays Capital in London), Joe became a teacher before taking the Northcoders course in 2017. Since then, he has worked in data engineering roles at AutoTrader, Greensill Capital and Inawisdom (now part of Cognizant). Since 2022, he has been responsible for the Data Engineering course at Northcoders

Location We'll be at Northcoders at Manchester Technology Centre, who are kindly supplying 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. There is a lift to the venue and toilets are accessible.

SPONSORS

Thank you to NUMFocus for sponsoring Meetup and further support

Thank you to NorthCoders for an awesome venue and catering!

Lightning Talks are an opportunity for members of the community to share a short talk with the wider community - with or without slides!

Introduction to Open-Source Science (OSSci) - Tim Bonnemann (he/him)

Open-Source Science (OSSci) is a new NumFOCUS initiative – launched in July 2022 in partnership with IBM – that aims to accelerate scientific research by improving the ways open source software in science gets done (built, used, funded, sustained, recognized, etc.). OSSci connects scientists, OSS developers and other stakeholders to share best practices, identify common pain points, and explore solutions together.

The five OSSci interest groups to date cover domain-specific topics (chemistry/materials, life sciences/healthcare, climate/sustainability) as well as cross-domain topics (reproducibility, map of science), with more to be rolled out in 2024. This lightning talk will provide a brief overview of OSSci’s activities to date, our plans for 2024, and how you can get involved.

Tim Bonnemann, Community Lead, Open-Source Science (OSSCi) at IBM Research

AutoXAI4Omics: Automated eXplainable AI for Omics - Anna Paola Carrieri (she/her)

AutoXAI4Omics (https://github.com/IBM/AutoXAI4Omics) is a command line automated explainable AI tool that easily enable healthcare and life sciences scientists (e.g., biologists, bioinformaticians, clinicians) to perform prediction tasks from omics data (e.g., gene expression; microbiome data; SNPs) and any tabular data (e.g., clinical data) using a range of machine learning methods. As an example a scientist may quickly an end-to-end ML analysis to predict disease type or status from genomics data without having to code or understand the deep technical details of the ML pipeline. A broad technical team from IBM Research has developed, tested and validated the tool for -Omics use cases over a number of years

Anna Paola Carrieri, Manager, Healthcare and Life Science team in IBM Research UK

The floor will then be opened up to other community lightning talks!

We'll be at BabNQ, the capacity is limited to 60.

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. The event space is downstairs.

SPONSORS

Thank you to NUMFocus for sponsoring Meetup and further support