Demo

Product Owner, Product Recommendations

Michael Page
New York, NY Full Time
POSTED ON 4/16/2025
AVAILABLE BEFORE 5/14/2025

We are seeking a technical Product Owner to lead the development and scaling of our AI-powered recommendation engine across eCommerce brands, driving personalized shopping experiences and optimizing product discovery. The role involves collaborating with cross-functional teams to enhance machine learning models, ensure system performance, and maintain compliance with global privacy regulations.

Client Details

A major player in the cosmetics and skincare industry, operating a robust eCommerce platform to complement its physical retail presence. As a client, they are highly focused on delivering personalized shopping experiences through advanced AI-driven recommendations and customer-centric features. They prioritize scalability, data privacy, and seamless integration across multiple brands under their umbrella, offering a wide range of high-quality beauty products to a global audience.

They value innovative digital solutions that enhance customer engagement, optimize product discovery, and drive conversion rates while ensuring compliance with strict global privacy regulations like GDPR and CCPA. With a keen emphasis on data-driven insights and performance optimization, they are always looking for advanced technology solutions that improve both the customer journey and back-end infrastructure in a highly competitive eCommerce landscape.

Description

  • Define and execute the product roadmap for recommendation systems, focusing on scalability across multiple brands and platforms.

  • Collaborate with data science and engineering teams to enhance machine learning models for personalization.

  • Work with infrastructure teams to ensure recommendation systems are scalable, performant, and cost-effective.

  • Lead technical discussions on system architecture, API integrations, and data pipelines.

  • Ensure compliance with global privacy regulations (e.g., GDPR, CCPA) in the development of recommendation features.

  • Use customer insights, A/B testing, and analytics to optimize and iterate on recommendation performance.

  • Balance algorithmic and business-driven strategies with merchandising and brand teams.

  • Establish KPIs to measure the effectiveness of recommendations and drive improvements.

  • Stay updated on AI, recommendation systems, and privacy trends.

  • Experience with cloud-based AI/ML Platforms such as AWS SageMaker or Google Vertex AI ect
  • Strong experience with SQL, Python, or other data querying and scripting languages
  • Act as the customer voice, ensuring recommendations improve the shopping experience and business outcomes.

  • Manage backlog grooming, sprint planning, and prioritization for high-impact deliverables.

Profile

A successful candidate for this role will have 5 years of product management experience, with a strong technical background in AI-driven personalization and recommendation systems. They should be proficient in machine learning models, data pipelines, and cloud infrastructure, with a proven ability to scale recommendation systems in high-traffic environments. The candidate will have strong analytical skills, experience with A/B testing, and a deep understanding of global privacy regulations. Excellent communication, stakeholder management, and Agile proficiency are essential, along with a customer-focused mindset to drive both business and user experience outcomes.

Job Offer

This opportunity offers a 12 month contract opportunity, 100% remote flexibility, and a quick start date of ideally May 5th.

No Third Parties Will Be Considered

MPI does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, marital status, or based on an individual's status in any group or class protected by applicable federal, state or local law. MPI encourages applications from minorities, women, the disabled, protected veterans and all other qualified applicants.

Salary : $75 - $85

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