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Data Science Product Manager Jobs in Texas (NOW HIRING)

Michaels Stores

Manager - Data Science

Irving, TX · On-site

Support Center - Irving The Manager - Data Science role is critical in helping to determine which CRM tactics most effectively drive long-term value with our customers. The ideal candidate will ...

Corva

Product Manager

Houston, TX · On-site

As a Product Manager, you will lead a team to develop high-impact solutions for the oil and gas ... Serve as a technical liaison between engineering, data science, and business teams, ensuring ...

Hp

AI Data Scientist - Enterprise AI

Austin, TX · On-site

$130K - $205K/yr

Demonstrates technical depth in LLMs, machine learning, and data science while maintaining a practical focus on implementation. * Communicates clearly with product managers, engineers, and ...

Hp

AI Data Scientist - Enterprise AI

Spring, TX · On-site

$130K - $205K/yr

Demonstrates technical depth in LLMs, machine learning, and data science while maintaining a practical focus on implementation. * Communicates clearly with product managers, engineers, and ...

DevRev

Data Engineer

Austin, TX · On-site

$113K - $136K/yr

Partner closely with Software Engineering, Data Science, Product Management, and other stakeholders to understand data requirements and translate them into robust technical solutions. * Define and ...

TBK Bank, SSB

Director of Data Science

Dallas, TX · On-site

In addition to hands-on technical leadership, this role may include managing data science talent ... Partner closely with product, analytics, and engineering teams to translate transportation domain ...

Triumph Financial

Director of Data Science

Dallas, TX · On-site

In addition to hands-on technical leadership, this role may include managing data science talent ... Partner closely with product, analytics, and engineering teams to translate transportation domain ...

Triumph Financial

Director of Data Science

Dallas, TX · On-site

In addition to hands-on technical leadership, this role may include managing data science talent ... Partner closely with product, analytics, and engineering teams to translate transportation domain ...

TBK Bank, SSB

Director of Data Science

Dallas, TX

In addition to hands-on technical leadership, this role may include managing data science talent ... Partner closely with product, analytics, and engineering teams to translate transportation domain ...

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All JobsData Science Product JobsData Science Product Manager JobsData Science Product Manager Jobs in Texas

Data Science Product Manager information

See Texas salary details

$48K

$148.5K

$183.5K

How much do data science product manager jobs pay per year?

As of Sep 1, 2026, the average yearly pay for data science product manager in Texas is $148,510.00, according to ZipRecruiter salary data. Most workers in this role earn between $131,400.00 and $183,500.00 per year, depending on experience, location, and employer.

What is a Data Science Product Manager?

A Data Science Product Manager is a professional who bridges the gap between data science teams and business objectives by guiding the development of data-driven products. They work closely with data scientists, engineers, and stakeholders to define product vision, prioritize features, and ensure successful product delivery. Their role involves understanding both the technical aspects of machine learning and analytics as well as user needs and business strategy. This ensures that data-powered products are effective, user-focused, and aligned with organizational goals.

How does a Data Science Product Manager typically collaborate with data scientists and engineers during a product lifecycle?

A Data Science Product Manager plays a crucial role in bridging the gap between business objectives and technical teams. Throughout the product lifecycle, they work closely with data scientists to define project goals, prioritize features, and translate business needs into actionable data-driven solutions. They also coordinate with engineers to ensure the seamless integration of machine learning models into products, address technical constraints, and facilitate communication between cross-functional teams. This collaborative approach ensures that data science initiatives are both technically feasible and aligned with overall business strategy.

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

To thrive as a Data Science Product Manager, you need a strong background in product management, data analytics, and a foundational understanding of machine learning, often supported by a degree in a technical or quantitative field. Familiarity with tools like SQL, Python, JIRA, and knowledge of data platforms and agile methodologies is typically required. Excellent communication, strategic thinking, and the ability to bridge technical and non-technical teams are vital soft skills. These competencies ensure successful product development, effective stakeholder alignment, and the delivery of impactful data-driven solutions.

What is the difference between Data Science Product Manager vs Data Analyst?

AspectData Science Product ManagerData Analyst
Required credentialsBackground in data science, product management, or related fields; often requires experience with machine learning and data-driven product developmentTypically holds a degree in statistics, mathematics, or business; skills in data visualization and basic analytics
Work environmentCollaborates with product teams, data scientists, engineers; focuses on developing data products and strategiesWorks with business units to interpret data, generate reports, and support decision-making
Employer and industry usageUsed in tech companies, e-commerce, and organizations developing data-driven productsCommon across finance, marketing, healthcare, and business intelligence roles

The main difference is that Data Science Product Managers oversee the development of data products and strategies, requiring a blend of product management and data science skills. Data Analysts focus on interpreting data and generating insights to support business decisions. Both roles are essential in data-driven organizations but serve different functions within the data ecosystem.

What are popular job titles related to Data Science Product Manager jobs in Texas?

For Data Science Product Manager jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Data Science Product Manager jobs in Texas look for?

The top searched job categories for Data Science Product Manager jobs in Texas are:

What cities in Texas are hiring for Data Science Product Manager jobs?

Cities in Texas with the most Data Science Product Manager job openings:

Data Science Product Manager jobs near you
Infographic showing various Data Science Product Manager job openings in Texas as of August 2026, with employment types broken down into 85% Full Time, 13% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $148,510 per year, or $71.4 per hour.

Product Manager (Specialized in Machine Learning)

Carter Support Services

Houston, TX • On-site

Part-time

Re-posted 16 days ago

Job description

Product Manager (Machine Learning)
Company: Carter Support Services
Location: Houston
Position Summary
We are seeking a Product Manager with deep experience in machine learning-driven products to lead the strategy, development, and lifecycle of ML-powered solutions. This role sits at the intersection of business, data science, engineering, and user experience, translating complex machine learning capabilities into scalable, valuable, and user-friendly products.
The ideal candidate understands both product management fundamentals and machine learning concepts, and can effectively guide teams through experimentation, model iteration, and production deployment while keeping a strong focus on customer outcomes and business impact.
Key Responsibilities
  • Define product vision, strategy, and roadmap for machine learning-based products
  • Translate business problems into ML product requirements and measurable success metrics
  • Partner closely with data science and engineering teams to guide model development, training, evaluation, and deployment
  • Own product discovery, including user research, hypothesis testing, and experimentation
  • Define and prioritize features using data, experimentation results, and business impact
  • Establish KPIs for ML products, including model performance, business outcomes, and user adoption
  • Manage product lifecycle from concept through launch, iteration, and scale
  • Communicate product strategy and progress to stakeholders and executive leadership
  • Ensure responsible AI practices, including fairness, transparency, and compliance considerations
Required Qualifications
  • 4+ years of product management experience, with at least 2 years working on machine learning or data-driven products
  • Strong understanding of machine learning concepts (e.g., supervised vs. unsupervised learning, model evaluation, training pipelines)
  • Experience working with data scientists, ML engineers, and software engineers
  • Ability to translate technical concepts into clear product requirements and user value
  • Experience defining success metrics and using data to drive product decisions
  • Excellent communication, stakeholder management, and prioritization skills
Preferred Qualifications
  • Experience launching ML products into production at scale
  • Familiarity with MLOps practices and model lifecycle management
  • Experience with cloud-based ML platforms (AWS, GCP, Azure)
  • Background in AI-driven products such as recommendations, forecasting, NLP, or computer vision
  • Knowledge of regulatory, ethical, and responsible AI considerations
Core Competencies
  • Strategic thinking with strong execution focus
  • Data-driven decision making
  • Customer-centric mindset
  • Ability to manage ambiguity and complex problem spaces
  • Strong cross-functional leadership
Why Join Us
  • Build innovative products powered by cutting-edge machine learning
  • Work closely with talented data science and engineering teams
  • High ownership and visibility across the organization
  • Competitive compensation, benefits, and growth opportunities

Apply