Product Owner (Recommendations)

Client: A global leader in cosmetics and luxury fragrances

Job Title: Product Owner (Recommendations)

Location: New York City, NY (Hybrid)

Job Description:

• We are seeking a technical and data-driven Product Owner, Product Recommendations to own and scale our recommendation engine across a portfolio of brands.
• This role requires a deep understanding of how recommendation algorithms & machine learning models operate and how to integrate those models for customer-facing experiences.
• You will work at the intersection of product, engineering, and data science to drive personalized shopping experiences and optimize product discovery.
• As a Product Owner, you will be responsible for scaling and standardizing recommendation capabilities across multiple eCommerce brands, ensuring alignment with both technical infrastructure and business objectives.
• You will collaborate with engineering teams to enhance system architecture, improve algorithm efficiency, and support high-traffic environments.
• Your day-to-day will focus on optimizing the scalability, performance, and adaptability of our recommendation systems across our digital ecosystem while ensuring compliance with global customer privacy regulations.

Key Responsibilities

• Define and execute the product roadmap for product recommendations, with a strong emphasis on scaling across multiple brands and platforms.
• Partner with data science and engineering teams to develop and enhance machine learning-based recommendation models for personalization at scale.
• Collaborate with infrastructure and platform teams to ensure recommendation systems are performant, scalable, and cost-effective.
• Drive technical discussions around system architecture, API integrations, and data pipelines to support seamless recommendation deployment.
• Ensure compliance with global privacy regulations (e.g., GDPR, CCPA) when designing and implementing recommendation features.
• Utilize customer insights, analytics, and A/B testing to measure performance and continuously iterate on recommendations.
• Work closely with merchandising and brand teams to balance algorithmic and business-driven recommendation strategies.
• Establish clear KPIs to track the effectiveness of recommendation features and drive continuous improvements.
• Stay informed about industry trends, emerging technologies, and best practices in AI-driven personalization, large-scale recommendation systems, and customer privacy.
• Act as the voice of the customer, ensuring that recommendation strategies enhance the shopping experience while driving business outcomes.
• Own backlog grooming, sprint planning, and prioritization efforts to ensure high-impact deliverables.

Required Qualifications

• 5 years of experience in product management, with a strong technical background in recommendation engines, AI-driven personalization.
• Strong understanding of machine learning models, recommendation algorithms, and AI-driven personalization techniques.
• Experience scaling recommendation systems across multiple brands or high-traffic digital environments.
• Deep familiarity with large-scale data processing, cloud infrastructure, and microservices architectures.
• Proficiency in API design, data pipelines, and real-time recommendation systems.
• Strong analytical skills with the ability to interpret complex data sets and make data-driven decisions.
• Experience working closely with engineering, data science, and DevOps teams to implement scalable solutions.
• Understanding of A/B testing, customer segmentation, and performance measurement.
• Knowledge of global data privacy regulations (e.g., GDPR, CCPA) and their impact on recommendation systems.
• Excellent communication and stakeholder management skills.
• Proficiency in Agile methodologies and product ownership best practices.
• Bachelor's degree in a related field or equivalent experience.

Preferred Qualifications

• Hands-on experience with recommendation engines, collaborative filtering, and reinforcement learning.
• Experience with cloud-based AI/ML platforms (e.g., AWS SageMaker, Google Vertex AI, or similar).
• Strong knowledge of SQL, Python, or other data querying and scripting languages.
• Familiarity with eCommerce KPIs, conversion optimization, and digital customer experience.
• Previous experience in a large-scale multi-brand eCommerce environment is a plus.