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Product Manager Personalization Jobs (NOW HIRING)

Turquoise

Senior Product Manager, Personalization

San Diego, CA · On-site

$134K - $177K/yr

We are seeking a systems‑minded, highly collaborative Senior Product Manager to architect and ... Why this Role Matters The Personalization team builds the foundational building blocks that the ...

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Product Manager Personalization information

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$51.5K

$159.4K

$197K

How much do product manager personalization jobs pay per year?

As of Jul 11, 2026, the average yearly pay for product manager personalization in the United States is $159,405.00, according to ZipRecruiter salary data. Most workers in this role earn between $141,000.00 and $197,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Product Manager Personalization, and why are they important?

To thrive as a Product Manager Personalization, you need a strong background in product management, data analysis, and user experience design, often supported by a degree in business, computer science, or a related field. Familiarity with A/B testing platforms, analytics tools like Google Analytics or Mixpanel, and personalization engines is typically required. Exceptional communication, stakeholder management, and problem-solving skills help drive cross-functional collaboration and innovative solutions. These abilities are crucial for delivering personalized experiences that increase user engagement and achieve business goals.

What does a Product Manager for Personalization do?

A Product Manager for Personalization is responsible for developing and optimizing products or features that deliver personalized experiences to users. They analyze user data and behavior to identify opportunities for customization, work closely with engineering and design teams to implement personalization strategies, and ensure these features align with business goals. Their role often involves prioritizing product enhancements, measuring the impact of personalization efforts, and staying updated on industry best practices. Ultimately, they aim to increase user engagement and satisfaction by making products more relevant to individual users.

How does a Product Manager Personalization typically collaborate with data scientists and engineers to deliver personalized experiences?

As a Product Manager Personalization, you'll work closely with both data scientists and engineers throughout the product development lifecycle. You'll define personalization goals, prioritize features, and translate customer insights into actionable requirements. Regular meetings with data scientists help you understand model capabilities and limitations, while collaboration with engineers ensures technical feasibility and smooth implementation. Open communication and cross-functional teamwork are key to iterating quickly and delivering impactful personalized experiences for users.

What is the difference between Product Manager Personalization vs Product Manager Data Analytics?

AspectProduct Manager PersonalizationProduct Manager Data Analytics
Required SkillsUser segmentation, A/B testing, UX designData analysis, SQL, statistical methods
Work EnvironmentCross-functional teams focusing on user experienceData-driven decision making, analytics teams
Industry UsageTech, e-commerce, mediaFinance, tech, marketing

Product Manager Personalization and Product Manager Data Analytics both focus on data-driven product improvements. Personalization emphasizes tailoring user experiences through segmentation and testing, while Data Analytics centers on analyzing data to inform product decisions. Both roles require analytical skills but differ in their primary focus and methods.

More about Product Manager Personalization jobs
What cities are hiring for Product Manager Personalization jobs? Cities with the most Product Manager Personalization job openings:
What states have the most Product Manager Personalization jobs? States with the most job openings for Product Manager Personalization jobs include:
What job categories do people searching Product Manager Personalization jobs look for? The top searched job categories for Product Manager Personalization jobs are:
Product Manager Personalization jobs near you
Infographic showing various Product Manager Personalization job openings in the United States as of July 2026, with employment types broken down into 85% Full Time, 13% Part Time, 1% Temporary, and 1% Contract. Highlights an 86% Physical, 1% Hybrid, and 13% Remote job distribution, with an average salary of $159,405 per year, or $76.6 per hour.

Product Manager - Personalization & Digital Products

Firstchoicedrivers

Phoenix, AZ

Full-time

Posted 6 days ago

Job description

PRODUCT MANAGER – PERSONALIZATION & DIGITAL PRODUCTS

LOCAL PHOENIX, AZ CANDIDATES ONLY – NO RELOCATION AVAILABLE

100% ONSITE – PHOENIX, AZ

NO VISA SPONSORSHIP AVAILABLE

OVERVIEW

We are seeking an experienced Product Manager to lead the strategy, development, and optimization of personalization capabilities across digital products and customer engagement channels.

This role will focus on building and scaling AI-driven personalization experiences across web, mobile, and marketing platforms. You'll work closely with engineering, data science, design, and business stakeholders to deliver customer-centric products that improve engagement, conversion, and revenue.

The ideal candidate combines strong product management expertise with a technical understanding of APIs, data platforms, system integrations, experimentation frameworks, and AI/ML-powered personalization.

NON-NEGOTIABLE REQUIREMENTS

Must currently reside within commuting distance of Phoenix, AZ

Must be able to work onsite 5 days per week in Phoenix, AZ

No relocation assistance available

No visa sponsorship available now or in the future

Minimum 5–7+ years in a dedicated Product Manager title with end-to-end roadmap ownership and product lifecycle management

Analyst, Associate, Intern, Co-op, Project Coordinator, Business Analyst, and similar roles do NOT count toward the Product Manager experience requirement

Experience must include consumer-facing web and/or mobile products

B2B enterprise platform experience alone does not meet this requirement

Hands-on experience partnering with Data Science teams to build, launch, and optimize ML-driven personalization features

KEY RESPONSIBILITIES

Define and execute the roadmap for personalization capabilities across web, mobile, and marketing channels

Identify opportunities to enhance customer experiences using data, AI/ML, and contextual insights

Align product vision with business goals such as engagement, conversion, and revenue growth

Build and scale personalization use cases including recommendations, segmentation, dynamic content, and cross-sell opportunities

Leverage customer and behavioral data to deliver relevant and timely experiences

Partner with Data Science teams to develop and optimize machine learning models

Own the end-to-end product lifecycle from ideation through launch and optimization

Collaborate with engineering, data, design, analytics, and business stakeholders

Manage product backlogs, prioritization, and delivery timelines

Create executive-level presentations, product narratives, and business cases

Drive A/B testing and experimentation initiatives

Track KPIs including engagement, CTR, conversion, and revenue impact

Work with APIs, data platforms, and system integrations to support scalable personalization capabilities

REQUIRED QUALIFICATIONS

Product Management Experience

5–7+ years of Product Management experience

Experience must be in a dedicated Product Manager role with ownership of:

  • Product roadmaps
  • Product strategy
  • Product lifecycle management
  • Feature prioritization
  • Product launches

Analyst, Associate, Intern, Co-op, and related support roles do not count toward this experience requirement

Consumer Digital Product Experience

Proven experience building and launching consumer-facing digital products

Experience must include:

  • Web products
  • Mobile products
  • Customer-facing experiences

B2B enterprise platform experience alone does not satisfy this requirement

AI/ML Personalization Experience

Hands-on experience partnering with Data Science teams to build, launch, and optimize ML-driven personalization features

Experience must include ownership of personalization capabilities such as:

  • Recommendation engines
  • Customer segmentation
  • Propensity models
  • Dynamic content experiences
  • Cross-sell recommendations

Experience must be in a Product Management ownership capacity, not solely engineering, analytics, or data science support

Technical & Functional Expertise

Strong understanding of:

  • APIs
  • Data platforms
  • System integrations
  • Digital product ecosystems

Experience working with machine learning concepts including:

  • Recommendation systems
  • Segmentation models
  • Propensity models

Experimentation & Analytics

Experience with A/B testing and experimentation frameworks

Strong analytical mindset with data-driven decision-making capabilities

Experience measuring and optimizing:

  • Engagement
  • CTR
  • Conversion
  • Revenue impact

Industry Experience

Background in one or more of the following:

  • Financial Services
  • Banking
  • Travel
  • Hospitality
  • E-commerce
  • Consumer Digital Products

Education

Bachelor's Degree required

PREFERRED QUALIFICATIONS

Experience with Generative AI tools and personalization applications

Exposure to personalization platforms and orchestration layers

Experience with marketing technologies and customer engagement platforms

Experience working within American Express or similar enterprise ecosystems

Experience supporting enterprise-scale digital product environments

COMPENSATION

$50.00 per hour (W-2)

WORK DETAILS

Location: Phoenix, AZ 85003

Work Arrangement: 100% Onsite

Employment Type: Contract

Local Phoenix Candidates Only

Relocation Assistance: Not Available

Visa Sponsorship: Not Available

WHY THIS OPPORTUNITY STANDS OUT

Opportunity to lead AI-powered personalization initiatives in a large enterprise environment

Ownership of customer-facing web and mobile product experiences

Direct partnership with engineering, data science, analytics, and business stakeholders

Exposure to machine learning, recommendation systems, experimentation frameworks, and Generative AI applications

High-visibility role influencing customer engagement, conversion, and revenue growth

Opportunity to shape personalization strategy across multiple digital channels