Key Duties & Responsibilities:

• Manage the delivery and maintenance of CarTrawler’s industry-leading Data Science & Revenue Management platform to increase ancillary revenues for CarTrawler and our partners;
• Manage the scoping, sizing, prioritisation and delivery of CarTrawler’s Market Makers platform – building tools to enable CarTrawler to better monetise our supply content, deliver an enhanced customer proposition and balancing any associated risks;
• Leading the development, testing and deployment of machine learning algorithms to optimise customer’s experience on CarTrawler’s booking engine through personalised merchandising, offers, upsells and content;
• Own the maintenance and development of CarTrawler’s real-time unit margin data table, ensuring data is timely, robust and updated to reflect new costs and revenue streams, including the development and usage of predictive models;
• Leading on the company's cross-functional Data Science & AI roadmap development and delivery, while providing thought leadership on the same both internally and externally to our partners
• Build a strong working relationship with Head of MLOps to shape the future vision of the Data Science & Revenue Management platform;
• Work with Trading and other business colleagues to define and prioritise the delivery of the Data Science roadmap;
• Provide market-leading statistical analysis, forecasting, predictive modelling, simulation and optimization. Deploy, monitor, provide insightful analysis on current initiatives – swiftly course correcting where necessary.
• Effectively communicating analyses, recommendations, status, and results to business management and executives in business terms
• Provide team leadership: Hire, directly manage, coach, and develop experts in Data Science and MVT. Set clear expectations (e.g., OKRs), provide regular actionable feedback (e.g., via performance evaluations), and maintain a high-performance and ownership culture.

People Management:

• Hiring, onboarding & successfully embedding new employees to enable them to thrive within CarTrawler.
• Providing ongoing feedback & coaching by having constructive development conversations with your team as part of our performance and development process.
• Providing clarity on company strategy and hold team accountable by having regular 121’s.
• Leads, motivates and inspires by role modelling our company values.

Knowledge and Skills:

• Experience: M.S. or Ph.D. in a relevant technical field, min 5+ years’ experience in a relevant role. Previous experience in eCommerce would be a significant plus. A minimum of 3 years as a people manager.
• Technical: Expert knowledge of Python and SQL; advanced understanding of statistical modelling, algorithms, data mining and machine learning;
• Commercial Acumen: strong understanding of business KPIs and value drivers, and the ability to understand how you can influence these through Data Science, able to balance trades offs across long- v. short-term and simple v. complex;
• Communication skills: Ability to communicate succinctly, efficiently, and effectively across forums and to diverse audiences on Data Science and MVT developments and results;
• Thought Leadership: strong knowledge of development and advancements in the Data Science and AI fields, with ability to use these insights and to look into the future to inform Data Science roadmap, drive proposition innovation and business best practice;
• High collaboration: works effectively across teams to capture expertise and deliver strong outcomes;
• “Talent magnet”: has the experience and skills to earn the respect of a very talented team and the people skills to nurture their continued professional development;
• Analysis: Extensive experience solving analytical problems using quantitative approaches;
• Intermediate/Advanced familiarity with Enterprise Architecture, Software Development and DevOps principles – CarTrawler’s Data Science algorithms are deployed real-time in a production environment;
• CarTrawler’s Data Science platform is Python based and our algorithms are served via a cloud hosted platform using AWS (Amazon Web Services). We store and use large quantities of well-structured data in our Snowflake data warehouse and extensively use tools such as Airflow, Git, Docker, Jenkins. The Head of Data Science needs to be comfortable working in this current architecture and eager to work with the wider Data Science team to evolve our Data Science platforms.