Manager, Marketing Science & Analytics
New
C
CrossmediaMedia Marketing Science
Remote, USAFull-TimeManager
Salary not disclosed
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Job Details
- Experience
- 3+ years
- Required Skills
- PythonSQLTableauData scienceData visualization
Requirements
- 3+ years of experience in marketing science, statistics, econometrics, data science, or another quantitative discipline.
- Strong foundation in statistics and hands-on experience applying analytical methods to real-world business problems.
- Proficiency in Python, with experience using tools such as pandas, statsmodels, scikit-learn, PyMC, Meridian, or similar.
- Strong SQL skills and experience working with large or complex datasets; cloud data warehouse experience preferred.
- Experience with marketing measurement, including MMM, incrementality, experimentation, causal inference, or related methodologies.
- Ability to independently manage analytical workstreams and client relationships while knowing when to bring in senior leadership.
- Experience managing, mentoring, or developing junior team members.
- Strong communication skills and the ability to explain complex analytical concepts to both technical and non-technical audiences.
- Curiosity, sound analytical judgment, strong attention to detail, and a commitment to continuous learning.
Responsibilities
- Lead marketing science and analytics workstreams across current clients, new business, and internal initiatives, managing projects from data and measurement through analysis, insights, and recommendations.
- Partner directly with clients and account teams to define measurement objectives, translate business questions into testable hypotheses, and develop rigorous analytical approaches.
- Apply statistical and data science methods including media mix modeling (MMM), regression, causal inference, experimentation, geo-lift/DMA holdout testing, Bayesian methods, segmentation, forecasting, and optimization.
- Build, interpret, and communicate statistical models and translate complex analyses into compelling, actionable stories for clients and internal stakeholders.
- Use Python and SQL to analyze data and build reproducible, well-documented analytical workflows.
- Develop dashboards, visualizations, and other data products using tools such as Tableau, Python visualization libraries, or Datorama.
- Lead and mentor Analysts and Data Scientists, providing guidance on prioritization, analytical approaches, coding practices, and professional development.
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