Data Science Manager
M
MonzoTechnology
London or UK remoteFull-TimeManager
Salary£100,000 to £130,000 + Incentive Awards tied to your performance
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Job Details
- Required Skills
- PythonSQLMachine LearningData scienceData analytics
Requirements
- Significant experience managing and developing Data Scientists.
- Strong strategic data leader who uses data to influence decisions and direction.
- Experience partnering with senior and executive stakeholders across different functions.
- Comfortable working autonomously in a fast-growing and evolving organisation.
- Strong understanding of Data Science approaches including experimentation, causal inference, statistical analysis and machine learning.
- Proficiency with tools and languages such as Python and SQL.
- Ability to choose the right analytical approach for a problem.
- Experience building credibility and influencing stakeholders without relying on authority.
- Strong product judgement and experience using Data Science to shape product development and strategy.
- Ability to balance technical excellence with pragmatic decision-making and business impact.
- Experience helping Data Scientists develop their technical, product and leadership capabilities.
Responsibilities
- Lead, develop and grow a team of exceptional Data Scientists and other Data professionals.
- Hire, coach and retain talented people while creating an environment where they can develop and do their best work.
- Set the Data Science direction for your area and identify where data can have the greatest customer and business impact.
- Partner with Product, Engineering and senior stakeholders to shape strategy and influence product direction.
- Bring analytical rigour to complex and ambiguous problems and help teams turn them into clear, actionable opportunities.
- Ensure teams are using the right analytical approaches, from experimentation and causal inference through to statistical modelling and machine learning.
- Help connect Data Science work to measurable customer, product and commercial outcomes.
- Work with Analytics Engineering, Machine Learning and other Data disciplines to ensure teams have the data, tooling and infrastructure they need.
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