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VP Engineering

Paris, Île-de-France
€80000 - €90000 per annum
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VP ENGINEERING
Paris, France
80-90K€/an

LA SOCIETE :

Cette start up développe depuis plusieurs années une plateforme e-commerce permettant à ses clients d'avoir accès à plus plusieurs millions d'annonces. En plein développement, elle cherche à structurer ses équipes pour assurer la continuité de l'évolution de leurs projets Data & Tech grâce à son futur VP of Engineering.

LE POSTE :

Rattaché directement au CTO, vous aurez pour rôle de :

  • Définir et encadrer la stratégie Data & Tech
  • Manager une équipe de 15 personnes (profils Data, DevOps et Backend) et accompagner les leads dans leurs fonctions
  • Faire monter en compétences les membres de l'équipe et prendre en charge son développement (gestion des recrutements)
  • Représenter votre équipe au sein de la société
  • Apporter votre expertise et intervenir la partie technique si nécessaire
  • Piloter et monitorer la production
  • Fiabiliser et faire évoluer le pôle Backend, DevOps et Data

VOTRE PROFIL :

  • Vous êtes diplômé d'une école d'ingénieur
  • Vous justifiez d'une expérience dans un poste similaire avec encadrement et management d'une équipe
  • Vous avez un solide background technique
  • Vous souhaitez vous investir dans un projet à long terme et participer au développement de la société
  • Vous êtes un leader bienveillant qui sait écouter son équipe et faire évoluer ses membres
  • Vous êtes un très bon communiquant et savez promouvoir en interne comme en externe les projets des équipes

COMMENT POSTULER :

Merci de me faire part de votre CV à jour et je vous recontacterai au plus vite

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101920/MB
Paris, Île-de-France
€80000 - €90000 per annum
  1. Permanent
  2. Data Management

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Using Data Ethically To Guide Digital Transformation

Over the past few years, the uptick in the number of companies putting more budget behind digital transformation has been significant. However, since the start of 2020 and the outbreak of the coronavirus pandemic, this number has accelerated on an unprecedented scale. Companies have been forced to re-evaluate  their systems and services to make them more efficient, effective and financially viable in order to stay competitive in this time of crisis. These changes help to support internal operational agility and learn about customers' needs and wants to create a much more personalised customer experience.  However, despite the vast amount of good these systems can do for companies' offerings, a lot of them, such as AI and machine learning, are inherently data driven. Therefore, these systems run a high risk of breaching ethical conducts, such as privacy and security leaks or serious issues with bias, if not created, developed and managed properly.  So, what can businesses do to ensure their digital transformation efforts are implemented in the most ethical way possible? Implement ways to reduce bias From Twitter opting to show a white person in a photo instead of a black person, soap dispensers not recognising black hands and women being perpetually rejected for financial loans; digital transformation tools, such as AI, have proven over the years to be inherently biased.  Of course, a computer cannot be decisive about gender or race, this problem of inequality from computer algorithms stems from the humans behind the screen. Despite the advancements made with Diversity and Inclusion efforts across all industries, Data & Analytics is still a predominantly white and male industry. Only 22 per cent of AI specialists are women, and an even lower number represent the BAME communities. Within Google, the world’s largest technology organisation, only 2.5 per cent of its employees are black, and a similar story can be seen at Facebook and Microsoft, where only 4 per cent of employees are black.  So, where our systems are being run by a group of people who are not representative of our diverse society, it should come as no surprise that our machines and algorithms are not representative either.  For businesses looking to implement AI and machine learning into their digital transformation moving forward, it is important you do so in a way that is truly reflective of a fair society. This can be achieved by encouraging a more diverse hiring process when looking for developers of AI systems, implementing fairness tests and always keeping your end user in mind, considering how the workings of your system may affect them.  Transparency Capturing Data is crucial for businesses when they are looking to implement or update digital transformation tools. Not only can this data show them the best ways to service customers’ needs and wants, but it can also show them where there are potential holes and issues in their current business models.  However, due to many mismanagements in past cases, such as Cambridge Analytica, customers have become increasingly worried about sharing their data with businesses in fear of personal data, such as credit card details or home addresses, being leaked. In 2018, Europe devised a new law known as the General Data Protection Regulation, or GDPR, to help minimise the risk of data breaches. 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