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Machine Learning Manager, Operations

Posted 6 days agoViewed

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💎 Seniority level: Manager, 4+ years

📍 Location: UK

💸 Salary: 115000.0 - 130000.0 GBP per year

🔍 Industry: Financial Services

🗣️ Languages: English

⏳ Experience: 4+ years

🪄 Skills: AWSBackend DevelopmentLeadershipPythonSoftware DevelopmentSQLAgileCloud ComputingData AnalysisMachine LearningPeople ManagementProduct ManagementSCRUMProduct OperationsCross-functional Team LeadershipAlgorithmsAPI testingData engineeringData scienceCommunication SkillsAnalytical SkillsCollaborationCI/CDProblem SolvingRESTful APIsMentoringAttention to detailOrganizational skillsWritten communicationAdaptabilityProblem-solving skillsEmpathyTeam managementStakeholder managementStrategic thinkingData modeling

Requirements:
  • You have experience managing teams of 4 or more high-performing Machine Learning professionals and owning Machine Learning systems in production.
  • You understand how ML systems work, how they should be designed based on the business problem they solve, and can communicate this to technical and non-technical people.
  • You have experience collaborating with senior business stakeholders and product teams to implement ML systems.
  • You know what makes a high-performing team and know how to get there. You care deeply about helping others achieve their goals and become the best Machine Learning Scientists they can be.
  • You have an empathetic leadership style, and you build strong, effective relationships.
  • You thrive working on ambiguous problems.
  • You want to be involved in building a product that you and the people you know use every day, with a product mindset that prioritises customer outcomes and data-informed decisions.
  • You’re adaptable, curious and enjoy learning new technologies and ideas.
Responsibilities:
  • You will head up machine learning for the whole Operations domain at Monzo, helping us to build up the vision, strategy, and team of machine learning experts for this area.
  • You’ll work across interdisciplinary squads, with Product Managers, Engineers and other Data colleagues (Data Analysts, Data Scientists, Analytics Engineers) to ensure we’re pursuing the most impactful machine learning opportunities, and tackling them with pragmatic, iterative, and high-quality systems.
  • You will lead the design, build and delivery of machine learning systems, working at the intersection of Data, Product, and Engineering, and ensuring that all systems we build are safe and appropriately validated.
  • You will support, coach, and develop high performing Machine Learning Scientists through regular 1:1s, continuous feedback and fostering relationships with other leaders at Monzo.
  • You will contribute to best practices: helping us become an exceptional place to work for ambitious, highly motivated people.
  • You’ll play a key role in scaling the impact of machine learning across Monzo: empowering Machine Learning Scientists to work across the end-to-end lifecycle of their models, including shipping the models they train into production, and contributing to how we define and build our workflows and tooling as we scale our discipline.
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🏢 Company: Monzo👥 1001-5000💰 Secondary Market 5 months ago🫂 Last layoff almost 5 years agoFinancial ServicesBankingWealth ManagementFinTech

  • Experience managing teams of 4 or more high-performing Machine Learning professionals.
  • Understanding of ML systems and ability to communicate their design based on business problems.
  • Experience collaborating with senior business stakeholders and product teams to implement ML systems.
  • Knowledge of what constitutes a high-performing team and how to develop it.
  • Empathetic leadership style and ability to build strong relationships.
  • Comfort with ambiguous problems and a customer-centric product mindset.
  • Head up machine learning for the whole Operations domain at Monzo, building the vision, strategy, and team.
  • Work across interdisciplinary squads to pursue impactful machine learning opportunities pragmatically.
  • Lead the design, build, and delivery of machine learning systems while ensuring safety and validation.
  • Support, coach, and develop Machine Learning Scientists through regular 1:1s and continuous feedback.
  • Contribute to best practices, scaling ML impact, and empowering scientists to handle model lifecycles.

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