Dyson X DSSG - DS & DE in Practice

Hi all, welcome back to DSSG'23! This month, we have Dyson's data team share their data science and engineering practice at their HQ, the historic St James Power Station. Refreshments will be provided.

A few house rules from Dyson:

1. Please note that we can only admit those that filled up the security pass form. Dyson will not admit those that did not fill up the form.
2. No parking at St James. The nearest parking is at vivo3.
3. Event will start at 7pm sharp. Late comers will not be permitted after 7.30pm
4. Please note that videography and photography will not be allowed at Dyson HQ.

Agenda

• 6.30 - 7pm: Networking + refreshments
• 7pm - 7.15pm: Welcome and intro
• 7.15 - 7.35pm: Data Science and Data Engineering – Mutually Exclusive? by Kenny Chong (Senior Data Scientist)
• 7.35pm - 8pm: Under the Hood - Data Engineering in Practice by Wei Gan (Senior Data Engineer)
• 8pm - 8.20pm: Leveraging Data Engineers for Data Science and Analytics by Kevin Teo (Data Engineer)
• 8.20pm - 8.30pm: Q&A and Networking

Synopsis
Data Science and Data Engineering – Mutually Exclusive?
Data science projects require persistent collaboration between organisational stakeholders and the data teams. Furthermore, data science pipelines differ largely across organisations and even projects. In this talk, Kenny will share about managing various challenges as a data scientist, scaling data science projects from 0 to 1 and the importance of data engineering.

Under the Hood – Data Engineering in Practice
Data engineering is an essential aspect of data science, so it's crucial for data scientists to understand data engineering practices to make better data-driven decisions. In this segment, we’ll be introducing the modern data stack: the tools, technologies and best practices used to build and maintain a data pipeline that is robust, accurate and reliable.

Leveraging Data Engineers for Data Science and Analytics
Data Engineers play a crucial role in enabling Data Scientists and Analysts to effectively leverage data for decision-making. We’ll discuss how to ensure data quality through various processes, to create and maintain a Data Catalog and Lineage that allows for easy access and traceability of data, as well as to support Contextual Exploratory Data Analysis by providing relevant data subsets and creating appropriate tools and artefacts that facilitate rapid and agile DS development.

Speaker Bio
Kenny Chong is a senior data scientist under the Data and Analytics team at Dyson. Before joining Dyson, Kenny worked at a HR AI startup, X0PA AI where he led a ML system design solution to match job seekers to jobs and his projects have served over 300 million API calls till date. Kenny has also worked as a freelance consultant exploring data science solutions, and he has also worked on a project with the Department of Gastroenterology and Hepatology from Changi General Hospital to help identify polyps in real time using computer vision.

Wei Gan is a senior data engineer under the Data and Analytics team at Dyson. With a diverse background in industries such as digital payments, online gaming, supply chain and manufacturing, she has built ETL pipelines, data lakes, and data platforms to enable businesses to make data-driven decisions. As a data enthusiast, Wei Gan is constantly seeking new and innovative ways to leverage data to drive business growth and improve operations.

Kevin Teo is a data engineer under the Data and Analytics team at Dyson where he builds and maintains data systems for sustainability reporting and manufacturing operations. Previously, Kevin was in the public sector where he developed and deployed machine learning pipelines to detect cybersecurity threats. He has also dabbled in Digital Forensics Incident Response (DFIR) and malware analysis. Outside work, Kevin enjoys DIY activities such as fiddling with electronics (building computers) and home improvement projects.