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Data Science Product Manager Jobs in Raleigh, NC

Envestnet

Lead AI Quality Assurance Engineer

Raleigh, NC · Hybrid

$125K/yr

Works with engineering, data science, product management, cybersecurity, legal and risk teams to validate AI-enabled products and operational processes. Continuously improves testing frameworks ...

Circle K

Data Product Manager, Retail Media

Raleigh, NC · On-site

Partner closely with the Group Product Manager to define and execute the data product vision ... Advanced degree in Engineering, Data Science, or related analytical field. * 7+ years of experience ...

Dlapiper

Data Scientist

Raleigh, NC · On-site +1

Prioritizes, scopes and manages data science projects for internal stakeholders and clients. * Mines and analyzes data to drive optimization and improvement of product development, marketing ...

Verily

Staff Product Manager, Care Console

Raleigh, NC · On-site

$150 - $200/hr

Uniquely positioned at the intersection of technology, data science, and healthcare, Verily ... product management experience. * Mandatory Provider-Facing Experience: A minimum of 3+ years ...

Cisco

Engineering Product Manager

Cary, NC · On-site

$154K - $160K/yr

Degree expected to be in Computer Science, Engineering, Data Science, Information Systems, or a ... management. * Experience owning product strategy, roadmap, requirements, launch planning, and post ...

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Showing results 21-40

All JobsData Science Product JobsData Science Product Manager JobsData Science Product Manager Jobs in Raleigh, NC

Data Science Product Manager information

See Raleigh, NC salary details

$50.1K

$155K

$191.5K

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

As of Sep 8, 2026, the average yearly pay for data science product manager in Raleigh, NC is $154,954.00, according to ZipRecruiter salary data. Most workers in this role earn between $137,100.00 and $191,500.00 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 Raleigh, NC?

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

What job categories do people searching Data Science Product Manager jobs in Raleigh, NC look for?

The top searched job categories for Data Science Product Manager jobs in Raleigh, NC are:

What cities near Raleigh, NC are hiring for Data Science Product Manager jobs?

Cities near Raleigh, NC 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 Raleigh, NC as of August 2026, with employment types broken down into 88% Full Time, 10% Part Time, and 2% Contract. Highlights an 79% Physical, 2% Hybrid, and 19% Remote job distribution, with an average salary of $154,954 per year, or $74.5 per hour.

Lead AI Quality Assurance Engineer

Raleigh, NC • Hybrid

Envestnet
See more jobs at Envestnetexternal

$125K/yr

Full-time

Medical, Retirement, PTO

Posted 25 days ago

Job description

Description

Job Location   

The primary work location for this role is Berwyn, Raleigh, Boston, Chicago, or Seattle with a hybrid work model.   

  

About Envestnet  

Envestnet is an adaptive WealthTech company that is redefining the future of wealth management by helping advisors meet the moment with its comprehensive technology, actionable insights, and industry leading support. Backed by over 25 years of experience and approximately $7.0 trillion in platform assets, Envestnet is trusted by over one third of financial advisors across leading banks, wealth managers, brokerages, and RIAs.   

   

For a deeper look at how Envestnet is shaping the future of financial advice, visit www.envestnet.com.   

   

The Team You’ll Join  

The Quality Assurance Engineering team plays a critical role in ensuring the reliability, security, and effectiveness of Envestnet’s technology solutions, with a growing focus on AI-enabled products and platforms. Working at the intersection of engineering, data science, product, cybersecurity, and business operations, the team develops and executes innovative testing and validation strategies that help deliver trusted experiences for clients and internal stakeholders alike. By championing quality, governance, automation, and continuous improvement, the team helps accelerate the adoption of emerging technologies while ensuring solutions are scalable, compliant, and built to meet the highest standards of performance and customer confidence.

How You’ll Contribute   

Ensures that artificial intelligence solutions are accurate, reliable, secure, compliant and aligned with business and client expectations. Combines traditional QA practices with AI / ML validation techniques to test data integrity, model performance, automation workflows and user outcomes. Works with engineering, data science, product management, cybersecurity, legal and risk teams to validate AI-enabled products and operational processes. Continuously improves testing frameworks, monitoring methodologies, governance standards and automation capabilities to support scalable and trustworthy AI adoption.

  • Leads testing efforts for moderately complex AI products, features and platform enhancements.
     
  • Designs advanced test plans covering model accuracy, bias detection, explainability and operational resilience.
     
  • Develops automated testing frameworks and monitoring approaches for AI systems.
     
  • Performs detailed analysis of defects, model drift and production quality issues.
     
  • Partners with cross-functional stakeholders to define acceptance criteria and quality standards.
     
  • Mentors junior analysts and reviews testing deliverables for quality and consistency.
     
  • Supports implementation of enterprise AI governance and risk management controls.
     
  • Recommends improvements to testing methodologies, tooling and operational processes.
     
  • Facilitates quality reviews, stakeholder workshops, model validation discussions, and testing strategy sessions.
     
  • Identifies operational, technical, compliance, and model-related risks and recommends mitigation strategies.
     
  • Leads validation activities for AI models, data pipelines, automation workflows, user-facing AI capabilities, vendors, tools, and third-party technologies.
     
  • Evaluates quality, reliability, security, governance, and compliance considerations associated with AI products and services.

What You’ll Need to Bring  

  • Candidates should demonstrate the relevant experience, skills, and capabilities needed to successfully perform in the role. Relevant experience may be gained through current responsibilities, prior roles, project work, leadership opportunities, or other comparable experiences.
     
  • Ability to evaluate complex problems, identify root causes, assess alternatives, and implement practical, scalable, data-driven solutions.
     
  • Demonstrated ability to establish and maintain productive relationships across business, technology, product, engineering, data science, and risk organizations.
     
  • Knowledge of process improvement techniques, operational workflows, dependency management, quality optimization, and governance practices.
     
  • Ability to communicate technical and non-technical concepts clearly to diverse audiences, including leadership stakeholders.
     
  • Experience coordinating cross-functional initiatives, managing dependencies, tracking progress, and delivering measurable outcomes.
     
  • Strong understanding of AI concepts, machine learning fundamentals, AI system capabilities, limitations, risks, and practical applications, with experience validating AI/ML models, Generative AI applications, LLM-enabled systems, or data science solutions.
     
  • Experience with automated testing frameworks, API testing, model evaluation, prompt testing, hallucination testing, data quality validation, AI governance controls, and regulatory, security, privacy, or responsible AI requirements. 

Why You’ll Enjoy Working at Envestnet  

Help shape the future of WealthTech. At Envestnet you’ll gain hands-on experience and collaborate with some of the industry’s brightest minds to deliver meaningful, innovative solutions that make a real difference. 

We value flexibility in how and where work gets done, and we recognize strong performance with meaningful rewards—because your contributions should drive both business success and your own personal growth. If you’re looking for a place where your work has impact, your development is supported, and your contributions are truly valued, Envestnet is where you can build your future.  

The opportunity is now!  

  

Sponsorship  

This position is not open to candidates requiring visa sponsorship  

  

Our Investment in You 

This role offers a base salary range of  $152,300 to $190,400. The range listed represents a good-faith estimate of base salary compensation for this position and does not include incentive compensation, equity or benefits. Individual pay will be determined based on factors including, but not limited to, relevant experience, skills, education, certifications, and geographic location, in accordance with applicable pay transparency laws.  This role is eligible for an additional incentive component as part of the total rewards package.   

 

We provide a comprehensive suite of benefits - subject to Envestnet’s plan eligibility rules - that support your overall well-being including, medical insurance, paid time off (PTO), 401k company match, paid parental leave, education reimbursement, disability coverage and mental health & wellness support. Our investment in you means supporting you professionally, financially, and personally at every stage of your journey with us.  Please visit our benefits page on our career site to learn more.  

   

Our Commitment to Inclusion & Belonging  

Envestnet is an Equal Opportunity Employer and is committed to creating an inclusive environment for all employees and applicants. We welcome and value individuals of all backgrounds and do not discriminate based on race, color, religion, creed, sex (including pregnancy or related medical conditions), gender identity or expression, sexual orientation, national origin, ancestry, age, disability, genetic information, military or veteran status, citizenship status, or any other status protected by applicable law. We encourage individuals from all backgrounds to apply.  

 

We strive to provide an inclusive application and interview process. If you are a candidate with a disability and require reasonable accommodation, please contact us at  careers@envestnet.com. Please include your full name, the title of the role you are applying for, and the accommodation necessary to assist you with the recruiting process.      

Recruitment Fraud 

At Envestnet, safeguarding the trust and safety of job seekers is a top priority. We are aware that scammers may impersonate Envestnet recruiters or create fake job opportunities to deceive candidates. Review the information on our recruitment fraud awareness page to help you recognize and avoid recruitment fraud. 

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