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Manager Data Scientist Jobs in Raleigh, NC (NOW HIRING)

Decision Scientist

Raleigh, NC · On-site

$118K - $178K/yr

... management skills. * Experience in higher education, student success, healthcare, or another mission-driven environment is preferred. Education * Bachelor's degree in Computer Science, Data Science ...

The Opportunity As part of the Operations Consulting team, you will apply advanced data science and ... As a Manager, you will lead teams and manage client accounts, focusing on strategic planning and ...

Data Program Manager

Durham, NC · On-site

$47 - $63.50/hr

The Data Program Manager oversees roadmap, budget, and timelines for enterprise data initiatives as ... Possess background in Business Administration, Project Management, Communications, Computer Science ...

New

Product Manager- Data Acceleration- Hybrid, Cary, North Carolina We're a leader in data and AI ... Bachelor's degree or higher, preferably in data science, computer science, or a related ...

Product Manager- Data Acceleration- Hybrid, Cary, North Carolina We're a leader in data and AI ... Bachelor's degree or higher, preferably in data science, computer science, or a related ...

Product Manager- Data Acceleration- Hybrid, Cary, North Carolina We're a leader in data and AI ... Bachelor's degree or higher, preferably in data science, computer science, or a related ...

Showing results 41-60

Manager Data Scientist information

See Raleigh, NC salary details

$44.7K

$160.4K

$236.7K

How much do manager data scientist jobs pay per year?

As of Sep 15, 2026, the average yearly pay for manager data scientist in Raleigh, NC is $160,411.00, according to ZipRecruiter salary data. Most workers in this role earn between $129,800.00 and $165,300.00 per year, depending on experience, location, and employer.

What is a manager data scientist?

Manager Data Scientists are professionals who oversee data science teams and projects within an organization. They combine advanced analytical skills with leadership abilities to guide data scientists, set project priorities, and ensure data-driven strategies align with business goals. In addition to technical expertise in data modeling, machine learning, and analytics, they are responsible for mentoring team members, managing resources, and communicating insights to stakeholders. Their role bridges the gap between technical execution and strategic decision-making.

What are the key skills and qualifications needed to thrive as a manager data scientist?

To thrive as a Manager Data Scientist, you need expertise in statistical analysis, machine learning, data modeling, and a relevant degree such as in computer science, mathematics, or statistics. Familiarity with tools like Python, R, SQL, cloud platforms (e.g., AWS, Azure), and experience with data visualization software and project management methodologies are commonly required. Strong leadership, effective communication, and the ability to mentor and guide teams are vital soft skills in this role. These competencies ensure successful project delivery, drive data-driven business decisions, and foster a productive, innovative team environment.

How does a manager data scientist typically collaborate with cross-functional teams to drive business outcomes?

As a Manager Data Scientist, you will work closely with teams such as engineering, product management, and business stakeholders to ensure data-driven solutions align with company goals. This collaboration often involves translating complex analytical findings into actionable insights, setting project priorities, and managing expectations. You will also facilitate communication between data scientists and non-technical teams to foster understanding and ensure successful project delivery. Building strong relationships and promoting a culture of data-driven decision-making are essential aspects of the role.

What is the difference between Manager Data Scientist vs Data Scientist?

AspectManager Data ScientistData Scientist
Required CredentialsBachelor's or Master's in Data Science, Statistics, or related field; leadership experienceBachelor's or Master's in Data Science, Statistics, or related field
Work EnvironmentLeads teams, manages projects, collaborates with stakeholdersAnalyzes data, develops models, reports findings
Employer & Industry UsageUsed in organizations with data teams, tech, finance, healthcareFound across industries, entry to mid-level roles

The main difference is that a Manager Data Scientist oversees data teams and projects, focusing on leadership and strategic planning, while a Data Scientist primarily conducts data analysis and model development. The manager role involves more coordination, mentorship, and stakeholder communication, whereas the data scientist role emphasizes technical skills and hands-on analysis.

What are the most commonly searched types of Data Scientist jobs in Raleigh, NC?

The most popular types of Data Scientist jobs in Raleigh, NC are:

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

Cities near Raleigh, NC with the most Manager Data Scientist job openings:

Infographic showing various Manager Data Scientist job openings in Raleigh, NC as of August 2026, with employment types broken down into 86% Full Time, 12% Part Time, and 2% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $160,411 per year, or $77.1 per hour.

Vice President, Data Science

Durham, NC

Fidelity Investments
Investment Management and Consulting Services • 10K+ employees

Full-time

Posted 11 days ago


Fidelity Investments rating

8.7

Company rating: 8.7 out of 10

Based on 274 frontline employees who took The Breakroom Quiz


Job description

Job Description:

Note: Fidelity will not provide immigration sponsorship for this position.

The Purpose of Your Role

Fidelity Workplace Investing is seeking an experienced Data Science leader to lead a team focused on powering intelligent, personalized digital experiences for our customers. This role will partner closely with product, engineering, design, and business leaders to identify high-value opportunities and deliver AI-powered solutions that drive meaningful customer and business outcomes.

As team leader, you will be responsible for advancing our AI strategy in this area, developing and implementing best practices, delivering machine learning and generative AI capabilities, and enabling the responsible adoption of emerging AI technologies. You will lead a highly skilled team of data scientists through the full AI lifecycle-from experimentation and model development to deployment, monitoring, governance, and continuous optimization.

The ideal candidate combines deep technical expertise with strong business acumen and has experience delivering AI solutions at scale. This includes personalization, predictive modeling, recommendation systems, large language models (LLMs), agentic AI systems, and responsible AI practices. You will consult with business leaders to help ideate and shape the next generation of Fidelity's personalized experiences.

The Skills You Bring
  • People management: Proven ability to mentor and coach data scientists on project delivery and long-term skill development.
  • Stakeholder and relationship management: Strong ability to translate business opportunities into AI-driven solutions that deliver measurable outcomes.
  • Cross-functional Collaboration: Partner with executive leadership, product, and engineering teams to integrate AI models into customer-facing products
  • Written and verbal communication skills: Ability to communicate complex AI concepts, risks, and opportunities to both technical and non-technical audiences.
  • AI Development: Expertise across the AI/ML lifecycle, including experimentation, feature engineering, model development, deployment, measurement, monitoring, and governance.
  • Modeling: Deep understanding of statistics, predictive modeling, recommendation systems, experimentation, causal inference, and optimization techniques.
  • GenAI: Experience evaluating, deploying, and governing generative AI solutions, including large language models, retrieval-augmented generation (RAG), AI agents, and multimodal AI systems.
  • Tools: Strong proficiency in Python, SQL, MLOps, and modern AI/ML development frameworks (e.g. AWS Sagemaker).
  • undefined
Education and Experience
  • Master's or PhD in Computer Science, Data Science, Statistics, Applied Mathematics, Engineering, or a related quantitative discipline.
  • 12 years of experience in artificial intelligence, machine learning, advanced analytics, data science, or related fields.
  • Significant experience leading teams, programs, and organizational AI initiatives.
How Your Work Impacts the Organization

AI is transforming how customers engage with their financial future. Your team will shape and scale the intelligent experiences that power Workplace Investing's digital platforms, combining machine learning, generative AI, and personalization capabilities to deliver timely, relevant guidance at moments that matter most. Through these innovations, you will help millions of participants build confidence, improve financial well-being, and achieve better retirement outcomes.

Fidelity's Onsite Working Model
Fidelity is transitioning to a full-time onsite working model through a phased rollout across regions and roles. Currently, some roles and locations require 100% onsite presence, while others require less. Onsite expectations are likely to evolve as the rollout continues. This transition does not apply to fully remote roles.

Certifications:Category:Data Analytics and Insights

Please be advised that Fidelity's business is governed by the provisions of the Securities Exchange Act of 1934, the Investment Advisers Act of 1940, the Investment Company Act of 1940, ERISA, numerous state laws governing securities, investment and retirement-related financial activities and the rules and regulations of numerous self-regulatory organizations, including FINRA, among others. Those laws and regulations may restrict Fidelity from hiring and/or associating with individuals with certain Criminal Histories.


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