HelloFresh is a company focused on optimizing audience management and signal strategies for their paid social marketing efforts. The Lead Product Manager, Growth will own the signal, audience, and data layer of a closed-loop growth system, architecting frameworks and running experiments to enhance performance marketing.
Responsibilities:
- Define and evolve the company’s north star signal framework by capturing, transforming, and activating high-quality intent signals, shifting from lagging conversions to leading indicators while driving experimentation to improve platform learning and bidding efficiency
- Build and scale a first-party audience intelligence system, including advanced segmentation, automated audience creation, governance models, and real-time syncing infrastructure to enhance targeting precision and operational efficiency
- Own end-to-end signal integration strategies across major ad platforms, defining event hierarchies, optimizing signal quality and compliance, and shaping how algorithms interpret and act on company data
- Develop and manage a continuous Signal → Model → Decision → Feedback loop, ensuring alignment between internal measurement and platform signals while enabling real-time optimization, model retraining, and incrementality validation
- Act as the accountable owner across Product, Data Science, Engineering, and Marketing, influencing senior stakeholders and driving a test-and-learn approach that prioritizes evidence-backed innovation before scaling solutions
Requirements:
- 6–8+ years in Product Management, with meaningful experience in Ad-Tech, Growth, or ML-driven systems
- Proven track record of owning 0→1 and 1→N platforms — not just features — with clear before-and-after business impact
- Strong product intuition paired with analytical rigor: you can hold a strategic vision and a data model in your head simultaneously and know when to trust each
- AI-native by default LLMs, AI coding assistants (Cursor, Copilot, or equivalent), and automation are part of your daily workflow, not aspirational tools
- Hands-on experience with conversion tracking, signal transmission, and attribution: you have personally configured a CAPI integration, designed an event deduplication scheme, and engineered a signal hierarchy
- Audience management depth: custom audience creation and syndication, lookalike seed design, lifecycle segmentation, first-party CRM-to-platform matching pipelines, and identity resolution
- Privacy and compliance fluency: GDPR, CCPA, iOS signal loss, and their practical implications for signal coverage, audience eligibility, and match rates
- Experience working with ML and Data Science teams on model-driven products: you can co-own model design, review feature engineering, and challenge modelling decisions with informed questions