Note: The job is a remote job and is open to candidates in USA. Dermalogica, a part of Unilever Prestige, is seeking a Technical Product Manager to lead marketing measurement for their luxury beauty portfolio. The role involves owning the marketing measurement product, utilizing AI to enhance measurement processes, and ensuring that insights drive investment decisions across brands.
Responsibilities
- Act as the central owner of marketing measurement across the Prestige portfolio
- Define and manage a single roadmap that covers MMM, attribution and incrementality testing and the AI capabilities that power them — prioritized by business impact and scalability
- Balance tradeoffs between rigor, usability and speed
- Partner with data engineering to ensure reliable, standardized inputs across media, revenue, promotions and external drivers — the foundation both the models and any AI tooling depend on
- Monitor data quality and resolve upstream issues before they reach the models or any AI layer built on top of them
- Own refresh cadence, versioning and recalibration strategies for MMM, attribution and incrementality
- Use AI to automate and accelerate the measurement lifecycle itself — e.g., agents that QA inputs, flag drift, automate model refresh runs, reconcile MMM vs. platform vs. incrementality results, and surface anomalies for human review
- Ensure outputs remain accurate, stable and aligned with business reality, with AI augmenting (not replacing) analytical judgment
- Translate ambiguous measurement pain points into clearly scoped AI use cases (e.g., a copilot for media planners to query MMM, an agent that explains why platform attribution disagrees with MMM, automated narrative generation for measurement readouts)
- Prioritize based on business value, feasibility and data readiness — and say no to anything outside the measurement remit
- Personally design and build AI agents and agentic workflows that operationalize measurement — e.g., MMM/attribution reconciliation copilots, budget reallocation recommenders grounded in MMM outputs, scenario-planning assistants, automated insight summaries for brand teams
- Prototype quickly using agent frameworks (e.g., LangGraph, CrewAI or similar), LLM APIs (OpenAI, Claude, etc.) and lightweight front-end tooling (e.g., Gradio, Chainlit)
- Validate cheaply, then partner with Data Science & Analytics and IT to productionize what works — with clear inputs, outputs, success metrics and a plan to maintain it beyond the pilot
- Own how measurement outputs — and the AI tools that interpret them — are delivered and used
- Partner on dashboards, planning tools and budget allocation frameworks (e.g., Power BI media dashboards, MMM scenario planners, AI-driven measurement copilots embedded in those tools)
- Ensure outputs are clear, actionable and aligned to brand and portfolio workflows
- Drive adoption of the measurement stack — both the underlying models and the AI tools layered on top — across brands through training, playbooks and embedded workflows
- Educate stakeholders on interpretation and limitations of both measurement outputs and AI assistance; reconcile and communicate differences between MMM, platform reporting and other approaches
- Track adoption and outcomes; iterate until measurement (with AI as the enabler) is genuinely embedded in how investment decisions get made
- Translate measurement outputs into clear recommendations for investment decisions, using AI to scale the speed and consistency of those recommendations across brands
- Partner with brand marketing teams to inform budget allocation and channel strategy
- Track the impact of measurement-driven decisions over time
Skills
- 6–10+ years in product management, marketing analytics, marketing science or a closely related technical/analytics role
- Proven, hands-on experience building AI or LLM-based solutions applied to analytics, measurement or decision-support — not just familiarity with the concepts
- Comfortable in Python, working with APIs and data pipelines
- Track record of taking measurement and/or AI ideas from concept to working, adopted solution
- Strong understanding of paid media and performance marketing
- Strong data fluency including SQL, BI tools (Power BI or Tableau), and familiarity with BigQuery or Databricks and Python or R
- Bachelor's degree or equivalent experience in a quantitative, business or related field
- Hands-on experience building AI agents or agentic workflows (e.g., LangGraph, CrewAI, AutoGen or similar) strongly preferred
- Strong understanding of marketing science principles (MMM, attribution, incrementality) and how they apply to real-world decision making; hands-on experience with at least one strongly preferred
Company Overview
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