Product Owner, Product Recommendations

Job Title: Product Owner, Product Recommendations

Position Type: Long-term contract ongoing, and potential to convert if/ when headcount becomes available

Location: 100% remote

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.