Data Science Senior Principal

Lead a team of data scientists, providing mentorship and guidance on daily tasks, fostering professional development and capability growth. Oversee the implementation of Continuous Integration/Continuous Deployment (CI/CD) pipelines, ensuring deliverables meet project milestones and quality standards. Apply advanced machine learning, forecasting, and statistical analysis techniques to drive experimentation and innovation on data science projects. Lead the experimentation and implementation of new data science techniques for projects, ensuring alignment with internal and external customer objectives. Communicate project status, methodologies, and results to both technical teams and business stakeholders, translating complex data insights into actionable strategies. Facilitate data science team discussions, providing technical expertise on current methods and guiding decision-making for optimal outcomes. Contribute to strategic data science initiatives, influencing the direction of key projects and aligning team efforts with broader business goals. Encourage collaboration across teams and functions to ensure seamless integration of data science solutions into business processes and technology platforms. Foster Team Excellence: Lead and manage a multidisciplinary team of data scientists, machine learning engineers, and GenAI developers, ensuring they are empowered to deliver high-quality, scalable solutions. Quality Assurance: Establish and enforce best practices for coding, model development, and deployment processes to ensure all outputs meet organisational standards. Performance Management: Conduct regular 1:1s, performance reviews, and provide constructive feedback to support individual and team growth. Collaboration: Act as a bridge between squads and stakeholders, ensuring alignment and collaboration across teams to maximise impact. Upskilling: Develop and execute training plans to enhance the team's technical capabilities Mentorship: Provide technical mentorship and career guidance to team members, fostering a culture of continuous learning and professional development. Knowledge Sharing: Encourage and facilitate the sharing of knowledge, tools, and techniques within the team and across the organisation. 7+ years' leadership experience leading, managing or influencing multiple functions, geographies and stakeholders (ideally in a Global Digital Program). Experience managing a large, multi-cultural, diverse team. Significant previous experience creating and leading cross functional and multi-country business change programmes. Familiarity with modern data science tools and technologies such as continuous integration, build, deliver, test-driven development and automated acceptance testing. Experience of managing a portfolio of programmes and initiatives within a matrix structure, creating/delivering customer value propositions, and leading technology related programmes Communicating and inspiring confidence at a senior level with technical and non-technical audiences, with the ability to shape strong presentations and narratives that influence and commit people to change. Experience in multi-facility, international organisations with diverse multi-cultural, corporate cultures. Strong team engagement and motivation skills. You'll be adaptable and able to pivot in a dynamic environment, a digital enthusiast, a coach and a communicator. Ability to lead in a matrix and build capabilities in global teams. An advocate and ambassador of the 'test, learn, build or pivot' approach. Excellent understanding of machine learning techniques and algorithms. Knowledge of implementing Data Science, Machine Learning and GenAI solutions at scale. Experience with common statistical techniques and data science toolkits. Strong quantitative and analytical skills and experience with data visualisation tools. Applied statistics skills, such as distributions, statistical testing, regression etc. Experience with AWS, Databricks and Dataiku. Strong understanding of data structures and algorithms plus solution and technical design. Able to quickly pick up new programming languages, technologies, and frameworks Strong knowledge of applied data science. Significant expertise in machine learning algorithms and data science methods. Strong data wrangling experience with structured and unstructured data Experience with various programming and scripting languages, databases, processing and storage frameworks plus coverage with various hyperparameter tuning approaches Understanding and experience with CRISP-DM and Agile data science framework Ability to identify and resolve both people and process related issues