• Support technical and product decisions as a reference in Machine Learning/Artificial Intelligence, with a strong emphasis on NLP (Natural Language Processing) and LLMs (Large Language Models). • Design, implement and maintain data and ML pipelines, covering training, evaluation and inference, always focusing on performance, reliability and best practices. • Integrate traditional Machine Learning techniques with other AI solutions to solve complex, business-specific challenges. • Propose and implement technological innovations involving NLP, LLMs and cloud solutions (AWS). • Ensure that deliveries are robust, scalable and have measurable impact, preferably applying solutions in Big Data environments. • Actively collaborate with product, engineering and business teams, translating problems into AI/NLP solutions that generate real, measurable value.

• The Senior AI Data Scientist is a senior individual contributor role within Data Science, AI, & Agentic. This role is responsible for leading complex analytical, predictive, and applied AI workstreams, operating with a high degree of independence and serving as a trusted advisor on data science and AI strategy. • This role focuses on shaping and executing advanced modeling, experimentation, and applied AI solutions that address high-value business problems. The Senior AI Data Scientist translates ambiguous stakeholder needs into structured analytical approaches, model designs, evaluation frameworks, and actionable insights. They partner closely with cross-functional teams and stakeholders to ensure that analytical and AI-driven solutions are both technically sound and practically impactful. • At this level, the role combines strong quantitative expertise with deep modeling capability, rigorous experimentation practices, and thoughtful application of AI methods. The Senior AI Data Scientist influences analytical direction, improves delivery quality through best practices and reusable approaches, and elevates the overall effectiveness of data science workstreams across engagements.

• Operate and evolve the data platform (Databricks, Unity Catalog, data lake), ensuring availability, performance and cost control • Lead the full data lifecycle — ingestion, ETL/ELT and enablement — supporting billing and adoption pipelines with reliability and integrity • Establish and enforce data best practices: Governance, Modeling, Quality, Security & Privacy, Lineage and Accessibility • Define the team roadmap and prioritize requests, balancing competing needs of technical and business stakeholders • Collaborate with stakeholders to document clear data requirements and validate products with users • Monitor metrics and KPIs to guide decisions and drive continuous improvement of data products • Support the incorporation of AI into the team's workflows to accelerate performance • Lead and develop a cross-functional team of engineers, data scientists and analytics specialists — attracting, retaining and mentoring talent • Ensure billing and adoption pipelines operate with integrity, reliability and efficiency • Identify opportunities to scale and optimize the data operation

• Interpret raw data and form compelling narratives to draw meaningful insights that communicate our story and mission • Work with our Data Science team, as well as Product and Client Services, to shape Adelaide’s data into a clear and concise story • Help to formulate, develop, and optimize models in production • Help to support and augment our machine learning system to aid advertisers in buying efficient media • Support client management teams with data-driven insights based on millions of behavioral data points each day • Work with the engineering team to build efficient and robust data pipelines • Help direct experimental studies aimed at understanding advertising value across multiple channels and media environments