Senior Analyst, GenAI Marketing

This role is a hands-on analyst and product builder operating at the intersection of Marketing, data, product development, and generative AI. The team focuses on creating scalable AI products for Marketing, including experiment analysis, business reporting, campaign operations, and content workflows. Responsibilities include identifying high-value workflows, quantifying opportunities, translating business needs into product requirements, and building prototypes using SQL and Python. The role requires partnering with developers and Marketing teams to deploy solutions, leading user research and pilots, and driving adoption. Success involves launching AI products that improve productivity and business outcomes.

Identify recurring Marketing workflows where AI can improve speed, quality, scalability, or decision-making.

Quantify opportunities by establishing current effort, pain points, user base, and business value.

Translate business needs into clear product requirements, user journeys, milestones, and success criteria.

Build and test prototypes using SQL, Python, automation tools, and generative AI technologies.

Partner with developers and Marketing teams to turn prototypes into reliable products.

4–6 years of experience in analytics, product analytics, marketing strategy, business operations, consulting, product management, or a related field.

Bachelor’s degree or higher in a quantitative, technical, or business discipline.

Strong SQL skills and experience working independently with large or complex datasets.

Hands-on experience with Python, scripting, or workflow automation.

Experience defining hypotheses, designing experiments, and translating results into actionable recommendations.

Strong product thinking and ability to break ambiguous problems into structured workstreams.

Strong written and verbal communication skills in English.

Experience building GenAI applications, AI agents, or automated analytical workflows.

Familiarity with prompting, retrieval-augmented generation, APIs, model evaluation, and human-in-the-loop workflows.

Experience using AI-assisted development tools such as Codex, Cursor, Claude Code, or Google AI Studio.

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