Head of Data Science (London Area)

Current responsibilities of Head of Data Science

• Lead the data science strategy and team to deliver data science solutions e.g. retention, acquisitions and customer management using Python and Spark
• Lead the hiring to build a great pool of Data Scientists and Engineers for the team and support the recruitment activities of other data functions
• Motivate, inspire, coach and mentor colleagues within the Data Science team to help them develop technical excellence
• Define clear objectives for each individual managed, ensuring each individual has a personal development plan and regularly proactively works on it
• Support and mentor Data Scientists and Engineers with direct reports in their role as line managers
• Motivate, inspire, coach and mentor business partners and stakeholders to help them identify new transformational possibilities that Data Science enables
• Engage with senior stakeholders to identify and implement machine learning solution
• Work actively in the innovation team to catalogue, enable and propose innovation ideas
• A Head of Data Science is a responsible authority with the requisite knowledge to work across portfolios in the domain and help provide strategic technical direction that can optimise enterprise outcomes. This particular role focuses on the portfolios within the Legal Technology Solutions area, including Lawyer Productivity, Legal Digital Products, Knowledge Systems and Data Science. It is a key role in driving digital transformation and helping to ensure that the vision is being delivered in a rapid, iterative way while focusing on the overall experience to the users.
• Collaborate and work in tangent with different business and technical teams
• Identifying key data sources required to solve the business and undertaking data collection, pre-processing and analysis
• Big picture thinking - correctly diagnosing problems and productionising research.
• In charge of demonstrations, conducting demo trials, helping clients evaluate success criteria, and training users
• Compile, integrate, and analyse data from multiple sources to answer business questions
• Be updated with latest technological advances, evaluate their potential by working with the hands-on
• Quality assurance of team deliverables
• Partner management (Microsoft, start-up discussions)
• Manage scrum-of-scrum