Overview The Data Scientist is responsible for advanced audience development and technology enablement. The role requires the candidate to sift through big data by leveraging advanced statistical concepts and guide the client into the world of futureproofed technology. Working closely with client stakeholders and internal team leads are vital parts of the role, with accountability for the highest quality execution of a diverse array of client and project deliverables an imperative. The role functions as an expert technical point of escalation, an analytical problem solver, and a technical translator to internal account teams and clients. It provides ongoing strategic account direction/vision for technology, process, and data science. Responsibilities Lead the development and implementation of machine learning models and advanced analytics solutions for audience segmentation, predictive analytics, and strategic insights. Perform hands-on coding and code-reviewing in Python, including data manipulation, modeling, and automation of data pipelines. Work extensively with Databricks, AWS (Redshift), and SQL for data querying, ETL, and notebook development. Build and maintain dashboards and data visualizations, primarily using Tableau. Collaborate with cross-functional teams, support brand-specific analytics, and contribute to team knowledge sharing. Conduct data discovery, insight generation, and support strategic decision-making. Contribute in the creation and maintenance of documentation and best practices. Qualifications 6+ years of experience in the Advertising or Marketing industry Advanced English Level Working knowledge of advanced statistical concepts and machine learning techniques (logistic regression, k-means clustering, etc.) Understanding of experimental design and the concept of statistical significance in terms of test results Quantitative educational background (preferred advanced degree in Statistics and / or Data Science) Solid written and verbal communication skill with ability to communicate/translate complex concepts to non-technical audience Client management/consultative experience with both presenting and resolving issues Strong Python programming skills, including experience with relevant libraries for data science and analytics. Proficiency in SQL and database manipulation. Hands-on experience with Databricks and AWS (Redshift); Azure experience is acceptable, but AWS is preferred. Experience in building machine learning models and statistical analysis, including time series and audience modeling. Ability to create dashboards and visualizations in Tableau. #J-18808-Ljbffr