СШАBabylist
Principal Product Manager, Recommendations & Discovery
3 нед. назад
СШАSeniorRemote
mlpersonalizationmodel trainingfeature engineeringdata pipelinessearchrankingunit economics
Babylist is hiring a Principal Product Manager to lead personalization efforts in their consumer experience, focusing on ML-powered recommendations and discovery. The role involves strategic ownership and collaboration with ML engineering to enhance registry building for expecting parents.
About the company
- Babylist is an online platform that provides a universal service for creating wishlists for expecting parents.
- Babylist was built on editorial recommendations with deep baby gear expertise, trusted by millions of families.
- They utilize one of the richest first-party datasets in parenting to layer personalized, ML-powered recommendations.
- The company emphasizes early-stage ML investment and aims to build on editorial strength with personalization.
About the product
- Registry building is the core Babylist product involving products from swaddle to stroller with real stakes.
- Personalization problem includes latent intent, life-stage progression, multi-stakeholder gift dynamics, and deep declarative signal.
- The role owns recommendations and discovery, setting quality standards and a two-year horizon for personalization.
- The product integrates ML-powered systems to make registry building effortless and personalized across consumer decision points.
Responsibilities
- Own personalization end-to-end at Babylist: strategy, KPIs, quality bar, impact, and tradeoffs.
- Influence company strategy and investment decisions related to personalization beyond just the roadmap.
- Shape how the company thinks about personalization, aligning senior leaders and cross-functional teams.
- Partner closely with ML Engineering team, fluent in model behavior, tradeoffs, retrieval, ranking, candidate generation, and evaluation.
- Set the two-year horizon for product personalization and articulate maturity curve.
- Communicate clearly to fast-forward conversations and own impact rather than just celebrating launches.
Requirements
- Demonstrated product leadership inside ML-powered consumer products with experience in recommendations, personalization, or discovery at scale.
- Held roles like Principal PM, GPM, Director, or comparable with org-level influence over product and company strategy.
- Real B2C ML product depth with shipped recommendations, search, ranking, or personalization systems.
- Fluent understanding of ML lifecycle: data pipelines, feature engineering, model training, deployment, monitoring, iteration.
- Builder's instinct for early-stage ML investment focusing on few bets rather than breadth.
- Strategic foresight about personalization maturity curve and product vision.
- Deep customer expertise gathering qualitative and quantitative evidence into decisions.
- Commercial ownership understanding how recommendations drive registry completion, GMV, ad revenue, and retention.
- Ability to defend unit economics and collaborate with finance and data teams.
- AI-native daily practice using LLMs and AI coding tools for prototyping, analysis, and data querying.
- Adaptability to change, low ego, bias toward action, and working across teams without waiting for permission.