Marketing jobs in the US

Responsibilities

• Spot and prioritize high‑impact opportunities where data, experimentation, and visualization can clarify performance and guide marketing strategy.
• Design and evaluate marketing experiments and measurement frameworks (e.g., A/B tests, incrementality, pre/post, causal impact, casual inference, regression, multivariate analysis) to optimize spend, targeting, and creative across channels.
• Build models and analysis‑ready datasets using SQL and Python/R, working with large, multi‑source marketing and product data.
• Create clear engaging presentations and dashboards for technical and non-technical audiences.
• Automate recurring reporting and enable self‑serve analytics so partners can independently access trustworthy data and insights.

Requirements

• Bachelor’s degree in a quantitative field with 2–4 years of relevant experience, OR 5+ years in a comparable data analytics or data science role
• Strong proficiency with statistical analysis and data manipulation tools (such as SQL and a programming language like Python or R), and experience working with complex, high-volume datasets in a production analytics environment
• Proven ability to frame business problems as analytical tasks and deliver actionable insights
• Excellent communication and storytelling skills; you simplify complexity, highlight what matters, and influence decisions with clear visuals and narratives
• Demonstrated experience delivering data‑driven insights and recommendations that materially improved marketing or business performance

Preferred

• Graduate degree in a quantitative discipline (e.g., Statistics, Applied Mathematics, Computer Science, Econometrics, Operations Research) with a focus on advanced analytics, experimentation, or machine learning
• Performance/growth marketing understanding and hands‑on experience running and interpreting experiments (A/B tests, regression‑based analysis, incrementality, etc.)
• Demonstrated depth in designing and interpreting complex marketing experiments, uplift modeling, or causal inference approaches at scale, including for multi-channel or multi-touch attribution and budget optimization
• Proactive, self‑directed working style and a track record of learning and applying new analytical or modeling techniques
• Familiarity with AI-driven systems, tools, or workflows and applying AI/ML concepts to build scalable analytics pipelines and automate repeatable tasks

Benefits

• medical, dental, and vision coverage
• paid time off
• an Employee Assistance Program
• wellness and travel reimbursement
• travel discounts
• International Airlines Travel Agent Network (IATAN) membership