Nigel Aukland
Profile
Experienced in definition and management of data-related products for organisations in telecoms, retail and digital tech. My ambition is to work with the best data product managers and engineers in the field to define and engineer scalable data platforms for the future. Those that scale not just for volume but for use cases from enterprise analytics to machine learning. So that we can be ready for when the next business opportunity arises.
Education

MEng. Electrical and Electronic Engineering

1996 to 2000 at Imperial College, London

Recent Experience

Technical Product Owner - Data Engineering

July 2023 - present | Sony Interactive Entertainment (PlayStation), London, UK

Building a data engineering platform capable of supporting effective and innovative data engineering at PlayStation.

  • Platform Agility: Defining Infrastructure as Code to ensure agility in deploying new platforms for feature development.
  • Developer Agility: Data engineering frameworks to ensure effective development practices for 30+ engineers.
  • Pioneering concepts: Real time data streaming, customer attribute federation.

Data Product Manager

April 2014 - June 2023 | Sony Interactive Entertainment (PlayStation), London, UK

(Aug 2018 - June 2023)

    Staff Product Manager, ensuring that PlayStation's commercial business is supported with reusable, robust and scalable data products, both today and in the long term.
(Nov 2016 - Jul 2018)
    Product Owner for PlayStation Europe's core business performance reporting.
    Delivery of curated dashboards and reports to PlayStation Europe executive management.
(Apr 2014 - Oct 2016)
    Product Owner for a team delivering data products and insight relating to aspects of player behaviour across PlayStation devices and the PlayStation Network.
    Own the BI product backlog in a Scaled Agile Framework (SAFe) using Scrum.

Co-founder - Project Vola

December 2021 to April 2023

Full end to end system built primarily but not exclusively to profit from volatility in currency exchange markets.

  • Models to create value from volatility: Development of AI/ML time series models (LSTM neural networks: classifiers and regressors), logistic regression
  • Implementation of imbalanced classification techniques to capture high-value but infrequent trading opportunities involving: Custom loss functions, smote, custom feature engineering, grid search, scaling & transforming, custom metrics.
  • Training, validation and testing of models evaluated via statistical bootstrap techniques.
  • Codebase & Tools: Python, Tensorflow, neptune.ai.

Certifications