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Data Science Product Manager Jobs in Raleigh, NC

LexisNexis

Director, Data Sciences

Raleigh, NC · On-site

Manage departmental budget, resource allocation, and infrastructure needs for data science ... Record of successful collaboration with product, engineering, and business teams. * Proficiency in ...

LexisNexis

Director, Data Sciences

Raleigh, NC · On-site +1

Manage departmental budget, resource allocation, and infrastructure needs for data science ... Record of successful collaboration with product, engineering, and business teams. * Proficiency in ...

Deloitte

Data Scientist

Raleigh, NC

Analytical ability to manage multiple projects and prioritize tasks into manageable work products ... Stay up to date with the latest trends and technologies in data science and machine learning.

Advance Auto Parts, Inc.

Data Scientist

Raleigh, NC · On-site

Prototype new patterns; troubleshoot production issues across data, model, and infrastructure ... Bachelor's degree in Computer Science, Information Technology, Data Science, or Mathematics ...

Advance Auto Parts

Data Scientist

Raleigh, NC · On-site +1

Prototype new patterns; troubleshoot production issues across data, model, and infrastructure ... Bachelor's degree in Computer Science, Information Technology, Data Science, or Mathematics ...

DPR Construction

Technical Product Manager

Raleigh, NC · On-site

$162K - $187K/yr

The Product Manager will directly manage a team of Product Owners, while partnering with stakeholders, engineers, designers, data scientists and cross-functional teams to translate business needs ...

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All 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 Jun 14, 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.

Is 40 too late for data science?

A Data Science Product Manager can enter the field at age 40, as experience, domain knowledge, and skills like programming and statistical analysis are highly valued. Many professionals transition into data science roles later in their careers, and continuous learning through online courses or certifications can facilitate this shift.

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 80 20 rule in data science?

The 80/20 rule in data science suggests that roughly 80% of results come from 20% of the efforts or data. Data science product managers often focus on identifying the most impactful features or data subsets to optimize model performance and resource allocation.

Is 30 too late for data science?

A Data Science Product Manager can enter the field at age 30, as many professionals transition into data roles later in their careers. Success depends on acquiring relevant skills such as programming, statistics, and experience with tools like Python or SQL, regardless of age. Continuous learning and building a strong portfolio are key factors for career progression in data science.

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.

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.

Can a data scientist be a product manager?

A data scientist can transition into a product manager role, especially if they develop skills in project management, user experience, and business strategy. While the roles have different focuses—data scientists analyze data and product managers oversee product development—combining technical expertise with communication and leadership skills can enable a data scientist to succeed as a product manager.
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

Director, Data Sciences

LexisNexis

Raleigh, NC • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 28 days ago

LexisNexis rating

7.6

Company rating: 7.6 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

149th of 427 rated business services

Job description

** Please note that the selected individual for this role will be expected to work in our Raleigh, NC location from the time of joining. If you reside outside of the Raleigh region and you are unable or unwilling to relocate, then please consider other roles across our organization that might allow for remote locations. **
About our Team:
LexisNexis Legal & Professional, serving customers in over 150 countries with 11,800 employees worldwide, is part of RELX, a global provider of information-based analytics and decision tools for professional and business customers. Our company is a leader in deploying AI and advanced technologies to improve productivity and transform the legal market. We prioritize using the best models from today's top creators for each legal use case.
About the Role:
The Director, Data Sciences raises data-driven decision making of a function within a business unit through team leadership. They are also client/industry-facing, and they evangelize methodologies and best practices. They lead people and teams to develop an overall strategy for the execution of projects including creating use cases, roadmaps, alignment of stakeholders, and prioritization. This person acts as coach and leader of Managers and Data Scientists, as well as other resources. Influence should extend outside the director's immediate team to other teams within the director's peers. The Director drives development and implementation across the team to the business, rooted in a deep understanding of our customers, markets, trends, and challenges.
Responsibilities:
  • Strategic Leadership: Define and execute the data science vision and roadmap aligned with business objectives and technological advancement opportunities.
  • Team Management: Build, lead, and mentor a high-performing team of data scientists, fostering a culture of innovation, collaboration, and continuous learning.
  • Advanced Research Direction: Direct cutting-edge research initiatives in NLP, LLMs, and other emerging AI technologies to maintain competitive advantage. Champion innovation by staying current with the latest trends and techniques in data science and allocating resources to promising new approaches.
  • Machine Learning and AI Solutions: Lead the development and implementation of machine learning algorithms and AI solutions to solve complex business problems. Data Analysis and Modeling: Oversee advanced data analysis, modeling, and machine learning to develop predictive and prescriptive models that drive business outcomes.
  • Data Collection and Preparation: Establish protocols for collecting, cleaning, and preprocessing large datasets, ensuring data quality and reliability.
  • Data Visualization Strategy: Guide the creation of informative and compelling data visualizations to communicate results and insights to stakeholders effectively.
  • Cross-functional Collaboration: Partner with executive leadership and cross-functional teams to identify strategic opportunities and address business challenges.
  • Model Deployment and MLOps: Oversee the deployment of machine learning models into production environments, ensuring scalability and reliability.
  • Documentation Standards: Establish comprehensive documentation standards for projects, models, and code for knowledge sharing and reproducibility.
  • Stakeholder Management: Communicate the value and impact of data science initiatives to C-suite executives and business stakeholders.
  • Budget and Resource Management: Manage departmental budget, resource allocation, and infrastructure needs for data science operations.
  • Ethical AI Governance: Develop and enforce ethical guidelines and best practices for AI development and deployment.

Requirements:
  • Bachelors, Masters or Ph.D. in Data Science, Computer Science, Statistics, or a related field; MBA or additional business education is a plus.
  • 10+ years of progressive experience in data science, machine learning, or AI, with at least 8 years in leadership positions.
  • Demonstrated experience in managing and scaling data science teams of 15+ professionals.
  • Proven record of delivering high-impact AI and ML solutions that have driven significant business value.
  • Deep expertise with generative AI models and techniques (e.g., LLMs, GANs) for content generation and their practical applications.
  • Advanced knowledge of statistical analysis, machine learning algorithms, and data manipulation techniques at enterprise scale.
  • Experience in setting technical direction and implementing MLOps practices for model deployment and monitoring.
  • Strong business acumen with the ability to translate complex technical concepts into business value.
  • Excellent communication and leadership skills, with experience presenting to executive leadership.
  • Experience working in a global or multicultural environment
  • Record of successful collaboration with product, engineering, and business teams.
  • Proficiency in multiple programming languages relevant to data science (Python, R, etc.) and big data technologies.

Work in a way that works for you:
We promote a healthy work/life balance across the organization. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals.
Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive
Working for you:
We know that your wellbeing and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer:
  • Health Benefits: Comprehensive, multi-carrier program for medical, dental and vision benefits
  • Retirement Benefits: 401(k) with match and an Employee Share Purchase Plan
  • Wellbeing: Wellness platform with incentives, Headspace app subscription, Employee Assistance and Time-off Programs
  • Short-and-Long Term Disability, Life and Accidental Death Insurance, Critical Illness, and Hospital Indemnity
  • Family Benefits, including bonding and family care leaves, adoption, and surrogacy benefits
  • Health Savings, Health Care, Dependent Care and Commuter Spending Accounts
  • Up to two days of paid leave each to participate in Employee Resource Groups and to volunteer with your charity of choice

About the Business:
LexisNexis Legal & Professional® provides legal, regulatory, and business information and analytics that help customers increase their productivity, improve decision-making, achieve better outcomes, and advance the rule of law around the world. As a digital pioneer, the company was the first to bring legal and business information online with its Lexis® and Nexis® services.
#AIFluency
U.S. National Base Pay Range: $136,100 - $252,800. Geographic differentials may apply in some locations to better reflect local market rates.This job is eligible for an annual incentive bonus.
We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.
We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120.
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We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.
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