Head of Data Science

  • Location: London
  • Salary: £110,000 pa
  • Type: Permanent
  • Job reference: 20907

The Head of Data Science is a lead role with all the associated managerial and strategic goals, however, the ideal candidate will have to be hands-on and do analytics/coding as part of their day to day work.

Role Accountabilities

  • Lead, nurture, and grow a team of Data Scientists and Data Engineers
  • Supervise insights, machine-learning and engineering projects
  • Drive the creation and implementation of best practices for statistical data modelling, analysis, and machine learning; data exploration and reporting tools; and processes that allow data team to work efficiently within the product and the tech org
  • Define the overarching data strategy and vision for data pipeline, data products
  • Work closely with product management, product marketing, user-acquisition and development teams to ensure priorities and roadmap are aligned across the organisation

Experience & Qualifications

  • Strong experience in data science and analytics, ideally working with a consumer product
  • Significant experience managing, mentoring, and coaching teams of data scientists and analysts
  • The ability to filter complex and seemingly arcane analytics into clear, accessible, actionable insight
  • Excellent communication skills, and ability to work across multiple teams and levels within the organisation
  • Understanding of good software development practises: TDD, refactoring, pair-programming, SOLID design
  • Knowledge of Python and SQL (other programming languages is a plus)
  • A Data story teller and an appreciation for both the power and limits of data. You will be able to communicate your findings, orally and visually.
  • Experience of overseeing Big Data projects: managing risks and data security
  • Experience of leading data science, data discovery and machine learning projects
  • Experience in finding patterns in data and creating statistical models, data exploration, data visualisation and data mining
  • You will have statistical, mathematical, predictive modelling as well as business strategy skills to build the algorithms necessary to ask the right questions and find the right answers
  • A PhD in a quantitative discipline such as computer science, statistics, physics or mathematics. MBA is a plus

Technical Knowledge 

  • Analytics: SQL, jupyter/ipython notebooks, re.dash
  • Modelling: scikit-learn, stats-models, pymc3, tensor-flow
  • Data Engineering: python, SQL, Spark, Scala, Docker, AWS
  • Data Warehouse: AWS Redshift
  • Dashboards: D3.js, bokeh, re.dash, Tableau

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