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The Data Scientist designs and delivers advanced analytical solutions that power strategic decision-making across the organization. This role transforms complex data into actionable insights, predictive models, and scalable machine learning solutions that drive marketing performance, deepen customer understanding, and improve business outcomes. Working cross-functionally with strategy, media, client services, and engineering teams, the Data Scientist translates business challenges into data science initiatives and communicates results clearly to both technical and non-technical stakeholders. This role plays a critical part in elevating analytical rigor, innovation, and impact across the organization.
Job Responsibility:
Design, develop, and deploy predictive models, segmentation frameworks, and machine learning solutions to support marketing performance, targeting, and customer analytics
Analyze large, complex datasets to uncover insights that inform strategic and tactical business decisions
Build and maintain robust data pipelines to ensure clean, reliable, and well-structured data for analysis and modeling
Ensure model integrity and performance through validation, QA processes, documentation, and ongoing monitoring
Design and execute experiments (including A/B and multivariate tests) to evaluate campaign effectiveness and optimize outcomes
Partner with strategy, media, and client services teams to translate business needs into scalable, data-driven solutions
Present findings and recommendations through clear storytelling, visualizations, and executive-ready materials
Contribute to team development through collaboration, peer review, knowledge sharing, and cross-training
Stay current with emerging data science tools, techniques, and best practices, helping evolve the team’s capabilities and standards
Requirements:
3–5+ years of applied data science experience, ideally in marketing, media, or customer analytics environments
Advanced proficiency in SQL for complex querying and data manipulation
Strong Python skills for data analysis, modeling, automation, API integration, and production workflows
Hands-on experience with machine learning frameworks (e.g., scikit-learn, XGBoost) and cloud/data platforms (e.g., AWS, Azure, Snowflake)
Strong foundation in statistics, experimental design, and computer science principles
Experience building and deploying models in production environments
Familiarity with marketing use cases such as audience segmentation, attribution modeling, audience creation, and trade area analysis
Experience with Alteryx is a strong plus
Experience with visualization tools such as Tableau (or similar BI tools) is a plus
Strong problem-solving skills, attention to detail, and the ability to work independently and collaboratively
Excellent communication skills with the ability to simplify complex analyses for diverse audiences
Understanding of data privacy regulations and ethical considerations in modeling
Nice to have:
Experience with Alteryx
Experience with visualization tools such as Tableau (or similar BI tools)