Head of Enablement (Data Solutions) London, England
- London
- Permanent
- Full-time
- Customer Advocacy for Data Solutions: Champion the voice of the user - both internal teams and external clients - throughout the data product lifecycle. Foster strong relationships, actively gather feedback on data product usability and insights, and ensure data product strategy and development aligns with customer needs. Manage global hero product communities focused on data and AI tools, fostering active discussion, participation and support.
- Data Solutions Product Adoption Strategy: Support regional, market and client-based enablement leads in developing adoption strategies for their user bases, by creating a scalable approach and supporting resources to effectively drive usage of data and AI tools within the Data Solutions pillar. This includes enabling users to effectively leverage advanced analytics, predictive models, and privacy-enhancing technologies.
- Data Solutions Product Enablement & Training: Work with the Product Training teams to develop and deliver impactful trainings and resources specific to our data products, supporting materials, and communication strategies to equip users with the knowledge and skills to leverage complex data capabilities, interpret AI-driven insights, and understand data governance principles effectively.
- User Communication & Support for Data Solutions Product: Act as subject matter expert in collaboration with the Product Communications team to develop pillar-specific marketing and release communications for new data products, features, and AI model updates. Collaborate with the Product Support team to draft knowledge base materials and SOPs & SLAs for L1 & L2 support resolutions related to data ingestion, processing, and output.
- Data Solutions Product Adoption Measurement: Partner with the Product Measurement team to ensure that there are clearly defined key performance indicators for data application usage within the Data Solutions pillar and track key metrics/analyse data to identify areas for improvement and optimize adoption efforts for our data and AI tools.
- Data Product Feedback Loop: Collates and centralizes product feedback specific to data solutions to provide back to the pillar leadership team, working closely with regional, market and client enablement leads to gather any specific requirements, feedback and priorities related to data quality, model performance, and insight generation.
- Partnership & Collaboration: Build strong working relationships with key stakeholders across the organization, including the central deployment and enablement team and regional, market and client enablement leads. Foster cross-functional collaboration to ensure a unified approach to data product adoption and customer success, particularly with data science, engineering, and privacy teams.
- Growth Enablement for Data Solutions: By exception, in partnership with regional, market and client leads contribute to new business and client growth discussions, ensuring provide pitch support, demo scripts and walkthroughs as required to showcase our data products and AI capabilities in a clear and compelling way, emphasizing their value in driving predictive performance and strategic insights.
- Be Extraordinary by Leading Collectively to Inspire transformational Creativity.
- Create an Open environment by Balancing People and Client Experiences by Cultivating Trust.
- Lead Optimistically by Championing Growth and Development to Mobilize the Enterprise.
- Proven experience in a leadership role focused on customer success, enablement, or training within a technology-driven organization, with a strong emphasis on data products, analytics, or AI/ML solutions.
- Deep understanding of data platforms, AI/ML technologies, and complex data workflows, with the ability to act as a power user and advocate for best practices in data utilization and interpretation.
- Deep understanding of the product development lifecycle and deployment processes, specifically within data-intensive environments.
- Excellent communication and interpersonal skills, with the ability to engage and influence diverse stakeholders, including data scientists, engineers, and business users.
- A collaborative mindset, with experience working cross-functionally with product, engineering, data science, and client-facing teams.
- Analytical skills to track performance metrics, identify trends, and drive data-informed improvements, especially related to data product adoption and impact.
- A proactive approach to problem-solving, with the ability to manage multiple priorities in a fast-paced environment.
- Familiarity with data-driven media planning and buying workflows, audience segmentation, and marketing analytics is highly desirable.