Associate Director, Data Science

Job Description The Data Scientist Associate Director is responsible for advanced audience development and technology enablement. This role requires deep expertise in data science methodologies, client management, and cross‑functional collaboration to deliver high‑value insights and business impact. Working closely with client stakeholders and internal team leads is vital, with accountability for the highest quality execution of a diverse array of client and project deliverables. 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 and vision for technology, process, and data science. Responsibilities Guide clients in clean room strategy and enable the use of future‑proofed technology Create and oversee propensity model development using machine learning for net new and refresh of existing audiences QA and troubleshoot 1P onboarded data to ensure acceptable match rates with client systems Advance internal modeling practices to optimize core hour usage and drive activation efficiency Perform audience analyses on existing customer segments and collaborate across internal teams to present actionable insights Guide the development of statistically sound test designs, minimizing bias and delivering actionable outcomes Stay informed about evolving media landscapes, providing research and insights to media teams and clients Communicate insights effectively, ensuring understanding and application of data science outcomes by clients Build impactful presentations that outline the importance of analyses, the insights revealed, and recommended actions Drive organic revenue growth through cross‑selling and up‑selling data science products across client divisions and categories Index report Python script runs and maintenance for data organization that leads to more efficient analysis Develop and implement a test‑and‑learn roadmap to continuously refine strategies and optimize data‑driven decisions, ensuring clear measurement frameworks and actionable insights Create and manage deliverables against a detailed roadmap that aligns expectations with outcomes Provide a high‑value consultation layer on top of data science deliverables Qualifications 6–8 years of experience in advertising, marketing, or data science fields, with agency experience strongly preferred Quantitative educational background Nice to have: advanced degree in Statistics and/or Data Science Experience with Habu, LiveRamp, EPC, Snowflake cleanroom for audience design Advanced proficiency in SQL, Python, and statistical modeling techniques (e.g., logistic regression, clustering) to manipulate data and draw insights from large data sets Familiarity with cloud services (e.g., AWS, Redshift) and large‑scale data management Solid understanding of digital media buying, KPI development, and programmatic audience buying Proven ability to manage and present to clients, with experience resolving complex data‑related challenges Strong critical thinking and problem‑solving skills – a demonstrated ability to mine data for relevant and actionable insights Exceptional written and verbal communication skill with ability to communicate and translate complex concepts to a non‑technical audience Proven ability to manage cross‑functional teams and fast‑paced projects while meeting tight deadlines Proven hands‑on knowledge and experience 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 Experience in a cross‑functional team environment with agency experience a big plus Strong understanding of contemporary marketing analytics, advertising technology and research techniques, as well as an innovative vision on how the practice should evolve to keep pace with the ever‑changing marketing environment Strong client management and consultative experience with both presenting and resolving issues Specific attention to detail to ensure that data anomalies/mistakes are caught prior to delivery of the analysis to the client teams Outgoing and able to integrate with fast‑paced planning and activation teams Able to cultivate excellent relationships with clients and technology partners Ability to meet deadlines in a fast‑paced environment All your information will be kept confidential according to EEO guidelines. #J-18808-Ljbffr UNAVAILABLE