GALE
GALE is the world’s first and only Business Agency. We bring business strategy to brand storytelling to drive enterprise value. With expertise in strategy, media, CRM, creative, performance marketing, and technology, GALE creates integrated marketing systems and campaigns that grow businesses in significant ways. Founded in 2014, the agency has since been named AdAge’s Business Transformation Agency of the Year and Adweek’s U.S. Media Agency of the Year and has been recognized for its innovative creative at the Cannes Lions. We work with brands such as Delta, Uber, Starbucks, Chili’s, Hard Rock, MilkPEP, Diageo, Cotton, IHG and more. If you’re driven by a passion to build something great, a desire to innovate, and a commitment to achieve excellence in your craft, GALE is a great place for you! GALE has eight offices around the world, including New York, Toronto, Los Angeles, Austin, Denver, Kansas City, London, and Bengaluru. GALE embraces a hybrid, flexible workplace Manager, Media Analytics Experience Required: 8 – 10 years We are seeking a highly skilled and experienced Data Scientist to join our team. The ideal candidate will have a strong background in machine learning, experience in implementing Generative AI (GenAI) solutions, and expertise in media and marketing analytics. This role requires a blend of analytical, technical, and problem-solving skills to drive data-driven decision-making and innovative solutions. Key Responsibilities: Machine Learning & AI Implementation Develop and deploy machine learning models to address business challenges. Design, implement, and evaluate GenAI models to optimize workflows and generate actionable insights. Keep up to date with the key developments in the area of LLMs and GenAI Media & Marketing Analytics Analyze and interpret marketing performance data to identify trends, opportunities, and areas for improvement. Build attribution models, campaign analysis, and customer segmentation strategies. Data Analysis & Visualization Create insightful dashboards and visualizations using tools like Tableau, Power BI, or similar. Present data-driven insights to technical and non-technical stakeholders. Data Processing & Management Work with large datasets to preprocess, clean, and transform data for analysis. Write optimized SQL queries to extract and manipulate data from databases. Collaboration & Stakeholder Management Collaborate with cross-functional teams, including marketing, product, and engineering, to drive data-centric decision-making. Communicate technical solutions effectively to non-technical stakeholders.