• Develop, validate, monitor, and evolve statistical, predictive, and Machine Learning models to support strategic business initiatives • Explore, analyze, and interpret large volumes of structured and unstructured data, turning them into actionable insights for decision-making • Conduct analytical studies and build models to understand customer behavior, identify patterns, and generate business opportunities • Design and implement scalable analytical solutions, ensuring result quality, efficiency, and reliability • Perform exploratory data analysis, hypothesis testing, and impact assessments to support strategic decisions • Identify opportunities to optimize processes using Data Science, Statistics, and Artificial Intelligence techniques • Work with data from various internal and external sources, ensuring integration, consistency, and data quality • Collaborate with Business, Data Engineering, and Technology teams to understand requirements and translate challenges into analytical solutions • Monitor the performance of models in production and propose continuous improvements to ensure accuracy and efficiency • Research, evaluate, and apply new methodologies, algorithms, and technologies related to Artificial Intelligence, Machine Learning, and Analytics to promote innovation and advance data solutions.

• Lead the strategy and delivery of predictive models that improve customer acquisition, marketing performance and long-term commercial value. • Partner with Marketing, Product and Commercial teams to apply Data Science to real business problems. • Work closely with Engineering and ML Ops to ensure models become reliable, production-ready products. • Lead and develop a growing team of Data Scientists while building trusted relationships across the business. • Represent Forbes in strategic conversations with technology partners while staying connected to advances in AI, machine learning and marketing science.

• Lead the strategy, roadmap and engagement initiatives for the core data visualization and data preparation ecosystem (BigQuery, Looker, and Looker Studio). • Guide the adoption cycle and curation of conversational data solutions (conversational analytics/CA) as a layer that provides agility and technology agnosticism. • Design, track, and evolve the directorate's scorecard of value and efficiency indicators, translating telemetry and analytical logs (e.g., reuse rates, autonomy and usage fidelity) into clear executive reports. • Drive planned cleanup and decommissioning of obsolete or idle analytical products at the edge, reducing clutter and noise in the environment. • Oversee team-built products, including Environment Cost Monitoring and Auditing and an AI-based Tools Migration Accelerator. • Lead alignment rituals and problem-discovery sessions with data leaders to ensure the roadmap solves the Group's real analytical bottlenecks.

• Partner with Trade leaders to solve complex business problems using data, analytics, and quantitative decision-making • Translate ambiguous business questions into analytical frameworks • Develop AI-powered tools and workflows • Serve as a trusted advisor to business stakeholders • Design and deploy Agentic AI solutions via APIs • Rapid hypothesis generation, statistical analysis, experimentation, forecasting • Communicate clear recommendations that drive measurable business outcomes