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What does the MLOps pipeline at a London-based FinTech startup, TrueLayer, look like?  

London-based fintech start-up TrueLayer decided to use Machine Learning instead of a rule-based system in mid-2019, and in our 7th meetup, we spoke to their lead data scientist, Alex Spanos, about everything that entailed.   

During the meetup, we dove into how TrueLayer architected their MLOps pipeline for their Open Banking API: more specifically, which tools they use and why, what prompted them to use machine learning, and how Alex sees the role of a Machine Learning Engineer. Alex has led the hiring process of Machine Learning Engineers and shared learnings on candidates and businesses alike.   

Alex is the Lead Data Scientist at TrueLayer, focusing on building Open Banking API products powered by data. Prior to TrueLayer, he built predictive models in Financial Services, used social data to predict the “next-big-thing” in fast-moving consumer Goods, and introduced Machine Learning techniques in subsurface imaging.  

His academic background is in Applied Mathematics & Statistics.  

Check out his blog entries for more info:

https://blog.truelayer.com/improving-the-classification-of-your-transaction-data-with-machine-learning-c36d811e4257

https://alexiospanos.com/hiring-machine-learning-engineers-part-1/

https://alexiospanos.com/hiring-machine-learning-engineers-part-2/

Connect with Demetrios on LinkedIn:  https://www.linkedin.com/in/dpbrinkm/ 

Connect with Alex on LinkedIn:  https://www.linkedin.com/in/alexspanos/

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