MLOps.community

Real-time Feature Pipelines, A Personal History // Hendrik Brackmann // MLOps Meetup #46


Listen Later

MLOps community meetup #46! Last Wednesday, we talked to Hendrik Brackmann, Director of Data Science and Analytics at Tide.

Join the Community: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://go.mlops.community/YTJoinIn⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

Get the newsletter: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://go.mlops.community/YTNewsletter⁠⁠

// Abstract:
Tide is a U.K.-based FinTech startup with offices in London, Sofia, and Hyderabad. It is one of the first and the largest business banking platforms in the UK, with over 150,000 SME members. As of 2019, one of Tide’s main focuses is to be data-driven. This resulted in the formation of a Data Science and Analytics Team with Hendrik Brackmann at its head. Let's witness Hendrik's personal anecdotes in this episode!
// Bio:
After studying probability theory at the University of Oxford, Hendrik joined MarketFinance, an SME lender, in order to develop their risk models. Following multiple years of learning, he joined Finiata, a Polish and German lender, in order to build out their data science function. Not only did he succeed in improving the risk metrics of the company, but he also learnt to manage a different department as interim Head of Marketing.
Hendrik's job as Director of Data Science and Analytics at business bank Tide is to oversee data engineering, data science, insights and analytics, and data governance functions of Tide.
// Final thoughts
Please feel free to drop some questions you may have beforehand into our Slack channel
(https://go.mlops.community/slack)
Watch some old meetups on our YouTube channel:
https://www.youtube.com/channel/UCG6qpjVnBTTT8wLGBygANOQ
----------- Connect With Us ✌️-------------   
Join our Slack community:  https://go.mlops.community/slack
Follow us on Twitter:  @mlopscommunity
Sign up for the next meetup: https://go.mlops.community/register
Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/
Connect with Hendrik on LinkedIn: https://www.linkedin.com/in/hendrik-brackmann-b2b5477a/
Timestamps:
[00:00] Introduction to Hendrik Brackmann
[01:54] Hendrik's background in tech
[03:22] First Phase of the three epic journeys of Hendrik
[08:05] Were there some hiccups you were running into as you're trying to make things better?  
[10:50] Any other learnings that you got from that job that you want to pass along to us?
[11:50] You were doing all batches at that point, right?
[12:35] Phase 2: of Hendrik's epic journey
[15:11] Did you eventually cut down at the time that it took?
[15:50] Breakdown of Transformation terminologies and their importance
[19:03] What are some things that you would never do again?
[20:32] How did you see things more clearly? [22:30] Phase 3: Moving on to Tide
[24:46] Have you only worked with teams with one programming language?
[30:47] Did you try to open-source solutions, or did you just go right out to buy it?
[33:12] What is real-time for you? How much latency is there? How much time do you need?
[37:18] At what stage did you realize to get the feature store?  
[40:09] What would you recommend from a maturity standpoint to get a feature store?
[41:20] Can you summarize some of the greatest problems that the feature stores solve for you?   
[42:22] What problems does a feature store introduce, if any?
[44:39] Where do the model and the feature start from the perspective of a system in engineering?
[49:15] You need good data management in feature stores
[50:21] Have you ever used or built any feature stores that explicitly handle units and do dimensional analysis on derived features?
[54:46] What kind of models do you have up at the moment, and how do you test and monitor, and deploy the models?

...more
View all episodesView all episodes
Download on the App Store

MLOps.communityBy Demetrios

  • 4.6
  • 4.6
  • 4.6
  • 4.6
  • 4.6

4.6

23 ratings


More shows like MLOps.community

View all
The a16z Show by Andreessen Horowitz

The a16z Show

1,095 Listeners

Software Engineering Daily by Software Engineering Daily

Software Engineering Daily

622 Listeners

Super Data Science: ML & AI Podcast with Jon Krohn by Jon Krohn

Super Data Science: ML & AI Podcast with Jon Krohn

302 Listeners

NVIDIA AI Podcast by NVIDIA

NVIDIA AI Podcast

332 Listeners

Data Engineering Podcast by Tobias Macey

Data Engineering Podcast

146 Listeners

Y Combinator Startup Podcast by Y Combinator

Y Combinator Startup Podcast

228 Listeners

Practical AI by Practical AI LLC

Practical AI

204 Listeners

Machine Learning Street Talk (MLST) by Machine Learning Street Talk (MLST)

Machine Learning Street Talk (MLST)

96 Listeners

Dwarkesh Podcast by Dwarkesh Patel

Dwarkesh Podcast

516 Listeners

No Priors: Artificial Intelligence | Technology | Startups by Conviction

No Priors: Artificial Intelligence | Technology | Startups

130 Listeners

This Day in AI Podcast by Michael Sharkey, Chris Sharkey

This Day in AI Podcast

228 Listeners

AI + a16z by a16z

AI + a16z

36 Listeners

Lightcone Podcast by Y Combinator

Lightcone Podcast

22 Listeners

Training Data by Sequoia Capital

Training Data

39 Listeners

The Pragmatic Engineer by Gergely Orosz

The Pragmatic Engineer

72 Listeners