Accelerating Data Science Deployment

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On Wednesday 27th February, Royal Mail would like to invite you to an evening of drinks, stimulating discussion and expert presentations by leaders in Data Science & Data Engineering.

Here's the agenda for the night:

6:30pm - 7pm: Registration, welcome drinks, pizza & networking.

7pm - 7.30pm: Dr Fabrice Durier

7:30pm - 7:55pm: Jorge Figueiredo

7:55pm - 8:05pm: Break

8:05pm - 8:35pm: Kannappan Sirchabesan

8:35pm - 9pm: Drinks & networking.

Here are the speaker/talk details:

Dr Fabrice Durier
Title: "Efficient Route Optimisation, the Future of Parcel Delivery"

Abstract: While the market leader in delivering parcels to British homes, Royal Mail is always working to adjust its operations to improve customer satisfaction. In this context, route optimisation tools can bring substantial value for increasing the service efficiency. In this talk, I will introduce the Vehicle Routing Problem (VRP) and show how meta-heuristics developed by the Operational Research community can be used in an Agile Data Science working environment. While demonstrating our interactive prototype, I will show how the exploration of many solutions of a given delivery set can provide parcel-sorting and delivery-ordering recommendations, while ensuring an cost-efficient service.

Bio: Dr. Fabrice Durier works as a Data Scientist at Royal Mail. A Cosmologist turned Data Scientist, Fabrice specialises in optimisation problems. Focusing on improving the management of Royal Mail Operations, he develops innovative models into simulations of cost minimisation.

Jorge Figueiredo
Title: "What is the role of a Data Engineering team?"

Abstract: In Advanced Analytics teams what should be the responsibilities of a Data Engineer to contribute to a high performant Analytics department?
How can Data Engineers enable other teams to delivery their work in production?
What is the role of DevOps and automation in general in this process?

In this talk I will go from the theory of some of the concepts and practical patterns of how a Data Engineering team can be structured to maximise performance and their different tradeoffs to allow autonomy and accountability for Data Science teams to deploy their models to a end user in Production.

Bio: Jorge Figueiredo is the Head of Data Engineering at Royal Mail. He is a software engineering leader with over 10 years of professional experience with passion about delivering great products on top of building and growing great engineering teams.

Kannappan Sirchabesan
Title: "BigQuery GeoSpatial"

Abstract: In a data warehouse like BigQuery, location information is very common. Geospatial data is a critical element of modern IoT, telematics, retail, and manufacturing workflows. Location of delivery vehicles, packages or the location of businesses or points of interest occur very commonly in the data and they can be used to derive useful business insights. BigQuery GIS provides the capability to ingest, transform, analyze and visualize geospatial data using GEOGRAPHY data types and functions in SQL. It also comes with a visualization tool BigQuery GeoViz to visually explore geo data on a map.

Bio: Kannappan Sirchabesan is a Cloud Data Engineer at Google helping large enterprises migrate big data and data science workloads to Google Cloud. He has been working on Big Data and Machine Learning technologies for the past several years.