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Fall Machine Learning Co Op information

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$25.3K

$42.3K

$87.4K

How much do fall machine learning co op jobs pay per year?

As of Jul 28, 2026, the average yearly pay for fall machine learning co op in Phoenix, AZ is $42,282.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,300.00 and $45,700.00 per year, depending on experience, location, and employer.

What is a Fall Machine Learning Co Op job?

A Fall Machine Learning Co-Op is a temporary, typically full-time position for students or recent graduates to gain hands-on experience in applying machine learning techniques. These roles usually involve working with data, training models, and optimizing algorithms under the supervision of experienced engineers or researchers. They are offered during the fall semester and can last several months. Companies use these positions to provide practical learning opportunities and assess potential future hires.

What can I expect from the day-to-day experience of a Fall Machine Learning Co Op?

As a Fall Machine Learning Co Op, you'll typically work with a team of data scientists and engineers on real projects that may involve data cleaning, model development, testing, and reporting insights. Your days might include collaborating in meetings, coding, analyzing data, and presenting findings to team members or supervisors. You'll receive mentorship from experienced professionals and have opportunities to participate in code reviews and brainstorming sessions. This structure helps you build technical skills, broaden your professional network, and gain a comprehensive understanding of how machine learning is applied in a business setting.

What are the key skills and qualifications needed to thrive in the Fall Machine Learning Co Op position, and why are they important?

To thrive as a Fall Machine Learning Co Op, you should have a solid background in programming (especially Python), statistics, and machine learning concepts, often supported by coursework or hands-on projects in computer science or related fields. Familiarity with tools like TensorFlow, PyTorch, and data analysis libraries such as pandas and scikit-learn is highly valued, while certifications in AI or data science can be a plus. Strong problem-solving skills, eagerness to learn, effective communication, and teamwork help you stand out in this role. These skills are crucial for contributing to real-world projects, collaborating with technical teams, and gaining valuable experience in a fast-paced, innovation-driven environment.

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Fall Machine Learning Co Op jobs near you
Infographic showing various Fall Machine Learning Co Op job openings in Phoenix, AZ as of July 2026, with employment types broken down into 1% As Needed, 77% Full Time, 18% Part Time, 1% Temporary, and 3% Contract. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $42,282 per year, or $20.3 per hour.

Product Manager - Personalization & Digital Products

Firstchoicedrivers

Phoenix, AZ

Full-time

Posted 23 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