Victor Robin, Ph.D.

Experience

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  COLAS

  Jan 2011 - Jul 2011

  Engineering Trainee in R&D
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  Université de Lorraine

  Oct 2011 - Mar 2013

  Teaching Assistant (PhD)
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  University of Exeter

  Apr 2013 - Sept 2014

  Teaching Assistant (PhD)
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  Dunnhumby

  Jan 2015 - now

  Responsible for the development and delivery of the components of dh Sphere involving big data and machine learning:* Insights: Learn about the health of a Brand to plan more effective media campaigns* Audiences: Choose audience segments from a predefined catalogue, including predictive audiences.* Measurements: Gauge campaign performance based on channel and campaign objectives.Responsibilities: Team development, hiring, staffing. Creation a software engineering culture, full-stack squads. Fast and short-cycle releases for continuous development and deployment. Development of high-performing teams Show less Responsibilities:- Head of dh Model Lab, dunnhumby’s first SaaS to simplify use of machine learning for retail industry- Lead a multifunctional development team- Product management (development, roadmap, prioritisation, vision)- Responsible for overall cloud architecture and Engineering side of the product- Responsible for the development and implementation of new machine learning features- Worked with InfoSec to ensure best security of the product and data- Worked with legal and privacy teams to ensure compliance and legal documents (T&C, etc…)- Worked with marketing teams to develop client material and online publicationsKey Achievements- Launched dh’s first SaaS, with a web and Enterprise versions- Migration of the entire product to Azure and created a multi-tenant and multi-region application- Reduced cost by leveraging serverless computing and microservices architecture- Removed need of dedicated Ops resources Technonologies:- Azure cloud service: ServiceBus, Container Instances, Azure Functions, ComosDB, Azure Apps- Docker, kubernetes, gRPC, React, Python, Go, Terraform Show less Responsibilities:• Lead development and deployment of dh's in-house automated machine learning tool for data scientists, on-premise and on cloud (GCP)• Lead a team of data scientists, backend engineers, frontend developers and data engineers• Roadmap, prioritisation and sprints planning• Backend architecture• Resource optimisation• Senior stakeholder managementKey Achievements:• Increased data scientist productivity by double figures %• Platform performance of machine learning pipelines in minutes• Used by 100s of data scientists internallyTechnologies & machine learning techniques:• Docker, kubernetes, gRPC, GCP, Spark• React, nodejs, Material UI• Multivariate Regression, Logistic Regression, Regularised Regressions, Support Vector Machines, Bagging, Boosting, Ensembling, Decision Trees (RF, ETC, GBM, XGBoost), Clustering, Optimization (Hyperopt) Show less • Won dunnhumby's Intrapreneurship Competition "The Million Pound Idea Challenge", • Development of automated machine learning pipelines in python for specific problems to increase the productivity of our teams• Pipelines support multiple methods and problems: Multivariate Regression, Logistic Regression, Regularised Regressions, Support Vector Machines, Bagging, Boosting, Ensembling, Decision Trees (RF, ETC, GBM, XGBoost), Clustering, Optimization (Hyperopt)• Python, Sklearn,XGBoost• Linux (CentOS), Docker, Continuous Integration Show less

  • Director of Engineering

    Jun 2022 - now

  • Cloud Engineering Manager

    Jul 2019 - May 2022

  • Research Data Science Manager

    Jul 2017 - Jun 2019

  • Senior Data Scientist

    Jul 2016 - Jun 2017

  • Data Scientist

    Jan 2015 - Jun 2016
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  Dunnhumby

  -

  Director of Engineering