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Data Science Project Manager Jobs in Raleigh, NC

MANAGER, DATA SCIENCE The Manager of Data Science will build and lead a focused, high-impact team ... Manage project-based work cycles (8-24 weeks) with clear start and end points * Ensure completed ...

MANAGER, DATA SCIENCE The Manager of Data Science will build and lead a focused, high-impact team ... Manage project-based work cycles (8-24 weeks) with clear start and end points * Ensure completed ...

Manager Data Science

Raleigh, NC · On-site

$115K - $192K/yr

Substantial experience in a senior data scientist role ... Experience leading complex projects and customer relationships. * Significant experience managing ...

Manager Data Science

Raleigh, NC · On-site +1

$115K - $192K/yr

Substantial experience in a senior data scientist role ... Experience leading complex projects and customer relationships. * Significant experience managing ...

Manager Data Science

Raleigh, NC · On-site

$115K - $192K/yr

Substantial experience in a senior data scientist role ... Experience leading complex projects and customer relationships. * Significant experience managing ...

Manager Data Science

Raleigh, NC · On-site +1

$115K - $192K/yr

Substantial experience in a senior data scientist role ... Experience leading complex projects and customer relationships. * Significant experience managing ...

Manager Data Science

Raleigh, NC · On-site

$115K - $192K/yr

Substantial experience in a senior data scientist role ... Experience leading complex projects and customer relationships. * Significant experience managing ...

Data Science Tutor

Durham, NC · Remote

$18 - $40/hr

... product management, marketing analytics, and healthcare informatics. * Curriculum Awareness ... Adapts instruction using Jupyter notebooks, real-world data sets, and end-to-end project workflows ...

Data Science Tutor

Chapel Hill, NC · Remote

$18 - $40/hr

... product management, marketing analytics, and healthcare informatics. * Curriculum Awareness ... Adapts instruction using Jupyter notebooks, real-world data sets, and end-to-end project workflows ...

Data Science Tutor

Raleigh, NC · Remote

$18 - $40/hr

... product management, marketing analytics, and healthcare informatics. * Curriculum Awareness ... Adapts instruction using Jupyter notebooks, real-world data sets, and end-to-end project workflows ...

The Data Science Services (DSS) department (6 librarians, 1 library specialist, plus graduate ... The position collaborates with colleagues and faculty on data-related initiatives and projects ...

The Data Science and AI Academy offers 1-credit project-based courses and customized non-credit courses on a variety of topics grounded in our ADAPT course model (All Campus Data Science Accessible ...

The Data Science and AI Academy offers 1-credit project-based courses and customized non-credit courses on a variety of topics grounded in our ADAPT course model (All Campus Data Science Accessible ...

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Data Science Project Manager information

See Raleigh, NC salary details

$16

$55

$78

How much do data science project manager jobs pay per hour?

As of Jul 13, 2026, the average hourly pay for data science project manager in Raleigh, NC is $55.90, according to ZipRecruiter salary data. Most workers in this role earn between $48.37 and $65.43 per hour, depending on experience, location, and employer.

What is the hottest job of the 21st century?

Data Science Project Managers are in high demand due to the rapid growth of data-driven decision-making across industries. They oversee data projects, coordinate teams, and require skills in analytics tools, project management, and communication. The role is considered one of the most sought-after careers in the 21st century for its impact and earning potential.

What is a Data Science Project Manager?

A Data Science Project Manager is a professional who oversees and coordinates data science projects from inception to completion. They act as a bridge between technical data science teams and business stakeholders, ensuring that project goals align with organizational objectives. Responsibilities include planning project timelines, managing resources, mitigating risks, and communicating progress. They also help define project requirements, monitor deliverables, and ensure that outcomes meet quality standards. Strong communication, analytical, and organizational skills are essential for this role.

Is 40 too late for data science?

For a Data Science Project Manager, age is not a barrier to entering or advancing in the field. Success depends on skills, experience, and continuous learning, such as mastering tools like Python or R and understanding business needs, regardless of age.

Can data scientists make $300k?

Data scientists can earn $300,000 or more annually, especially with extensive experience, advanced skills in machine learning and big data tools, and roles in high-paying industries or senior management positions. Achieving this level often requires a combination of technical expertise, certifications, and leadership responsibilities.

How does a Data Science Project Manager typically collaborate with data scientists and stakeholders throughout a project?

A Data Science Project Manager acts as a bridge between technical teams and business stakeholders, ensuring clear communication of goals, timelines, and deliverables. They facilitate regular meetings to discuss project progress, address any obstacles, and realign priorities as needed. By translating business requirements into actionable tasks for data scientists and providing updates to stakeholders, they help ensure that projects stay on track and deliver value. Effective collaboration often involves balancing technical feasibility with business needs, managing expectations, and fostering a cooperative team environment.

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

AspectData Science Project ManagerData Analyst
Required CredentialsOften requires a bachelor’s or master’s in data science, analytics, or related fields; project management certifications beneficialTypically holds a bachelor’s degree in statistics, mathematics, or related areas; certifications like Microsoft Excel or Tableau are common
Work EnvironmentLeads data science projects, collaborates with data scientists, engineers, and stakeholdersAnalyzes data sets, creates reports, visualizations, and supports decision-making
Employer & Industry UsageUsed in tech, finance, healthcare, and consulting firms managing data science initiativesFound across industries for data reporting, business intelligence, and operational analysis

In summary, a Data Science Project Manager oversees data science projects and manages teams, requiring project management skills and relevant certifications. A Data Analyst focuses on analyzing data and creating reports, with a more technical and analytical role. Both roles are essential in data-driven organizations but differ in scope and responsibilities.

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

To thrive as a Data Science Project Manager, you need a solid understanding of data science methodologies, project management principles, and usually a degree in computer science, statistics, or a related field. Familiarity with analytics tools (such as Python, R, SQL), project management software (like Jira or Trello), and certifications such as PMP or Agile/Scrum are often required. Strong leadership, communication, and problem-solving skills set top performers apart by enabling effective team coordination and stakeholder management. These competencies ensure projects are delivered on time, within scope, and generate actionable insights that drive business value.

Can a data scientist become a project manager?

Yes, a data scientist can become a project manager by developing skills in leadership, communication, and project planning. Gaining experience in managing teams, understanding project workflows, and obtaining certifications like PMP can facilitate this transition.
What are popular job titles related to Data Science Project Manager jobs in Raleigh, NC? For Data Science Project Manager jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Data Science Project Manager jobs in Raleigh, NC look for? The top searched job categories for Data Science Project Manager jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Data Science Project Manager jobs? Cities near Raleigh, NC with the most Data Science Project Manager job openings:
Manager, Data Science

Manager, Data Science

McGough

Raleigh, NC • On-site

Other

This job post has expired today. Applications are no longer accepted.


Job description

McGough is a respected partner that brings six generations of experience to high profile, unique and complex construction projects. We take great pride in our people and their extraordinary expertise in planning, development, construction and facility management. McGough employee tenure reflects the commitment and pride we share in our work. Ask anyone who knows us - the caliber of our people sets us apart.

MANAGER, DATA SCIENCE

The Manager of Data Science will build and lead a focused, high-impact team solving complex, high-value business problems through applied data science. This role defines how data science is used to improve how the business operates and makes decisions.

Operating in close partnership with business units, Central Analytics, and Data Engineering, this team functions as a high-leverage strike team, deploying into targeted, time-bound efforts (typically 8-24 weeks) to connect signals across the business and deliver measurable impact across cost, risk, and operational performance.

This role sets technical direction and ensures the team applies sound statistical and machine learning practices, while remaining grounded in real-world outcomes. The Manager is expected to stay hands-on, partially contributing to feature engineering, model development, evaluation, and production readiness to ensure solutions are not only technically sound, but usable and durable in practice.

Success in this role requires balancing analytical insight with operational reality, combining data with the experience and intuition of teams in the field to identify risks earlier, improve planning, and enable better decisions. This leadership role lives within the Digital Operations organization with responsibility for building and shaping the data science capability from the ground up as McGough continues to scale its investment in data, technology, and analytics.

QUALIFICATIONS:

Required:

  • Bachelor's degree in Data Science, Statistics, Mathematics, Engineering, or related field
  • 6-10+ years of experience in data science, advanced analytics, or applied modeling
  • Proven experience building statistical or machine learning models and delivering them in real-world business contexts with measurable outcomes
  • Strong programming experience in Python (or equivalent), including data manipulation, modeling, and evaluation
  • Experience leading or mentoring analytical teams
  • Experience working with version control (e.g., Git) and structured development practices
  • Strong communication skills translating technical outputs into business decisions

Preferred:

  • Master's degree in Data Science, Statistics, Mathematics, Engineering or related field.
  • Experience in complex operational environments (construction, manufacturing, logistics, etc.)
  • Experience selecting, building, and evaluating machine learning models across multiple problem types
  • Experience with optimization, simulation, or advanced forecasting
  • Familiarity with modern data platforms and engineering concepts
  • Experience applying machine learning in real-world business settings

Skills:

  • Strong problem structuring and analytical reasoning
  • Ability to operate effectively with incomplete or imperfect data
  • Experience with statistical modeling, machine learning, or optimization techniques
  • Experience with model validation, feature engineering, and performance evaluation
  • Ability to design reproducible analytical workflows and structured development practices
  • Strong Python or equivalent analytical tooling proficiency
  • Clear communication of complex concepts into actionable decisions
  • Ability to balance analytical rigor with practical application

CORE RESPONSIBLITIES:

Problem Framing & Solution Design

  • Translate loosely defined business challenges into structured analytical problems
  • Define success criteria tied to business decisions and measurable outcomes
  • Determine appropriate approaches including forecasting, optimization, or modeling
  • Identify key assumptions, constraints, and risks early

Advanced Analytics Delivery

  • Lead development of predictive models, scenario analysis, and decision frameworks
  • Guide team through ambiguous data environments without stalling on perfection
  • Ensure outputs are actionable, interpretable, and aligned to business use
  • Guide model evaluation, validation, and performance monitoring practices
  • Ensure models are designed for production use, including scalability, robustness, and maintainability
  • Accountable for the full analytical lifecycle from problem framing through model development, validation, deployment readiness, and post-deployment performance tracking
  • Ensure analytical outputs are reproducible, well-documented, and stable enough for business use beyond initial delivery

Operating Model & Intake Discipline

  • Define and enforce intake criteria focused on high-value, non-routine problems
  • Prioritize work based on business impact rather than request volume
  • Manage project-based work cycles (8-24 weeks) with clear start and end points
  • Ensure completed work is transitioned to BI, Data Engineering, or business teams for ongoing use

Model Development & Production Readiness

  • Guide development of models and analytical workflows that can be reused or extended beyond one-time analysis
  • Establish lightweight practices for versioning, validation, and documentation of analytical work
  • Ensure clear ownership and transition plans for models after delivery (handoff to BI, Data Engineering, or business teams)
  • Define when analytical solutions require further operationalization versus remaining project-based

Team Leadership

  • Build and lead a small team of advanced analysts or data scientists
  • Act as a player-coach, contributing directly to complex analytical work
  • Set standards for analytical rigor, clarity, and business relevance
  • Develop team capability in both technical and business-facing skills

Additional Responsibilities

  • Actively contribute as a member of the Digital Operations group, collaborating to support shared goals and objectives
  • Attend and participate in project management and other company meetings
  • Represent McGough professionally at all events, upholding company standards and serving as a positive ambassador
  • Attend company and team meetings, pursuing ongoing personal and professional development to enhance skills and performance
  • Collaborate across departments and with external stakeholders to ensure cohesive project execution
  • Actively support and participate in Lean events, promoting the McGough Way and fostering a culture of continuous improvement

OFFICE AND TRAVEL:

  • Position will be based in McGough's Raleigh, NC Office.
  • McGough supports a hybrid work schedule, with exact days and times defined by manager and team.
  • Travel is expected to be approximately 25% consisting of quarterly trips to McGough's headquarters for various training or team building activities. Additional travel to various national office locations may be required as determined by the individual and their manager.

PHYSICAL REQUIREMENTS:

The physical requirements listed here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Position involves sitting for extended periods of time at employee's workstation and during meetings as well as while traveling, either by plane or car. Employee needs to be able to lift to 20 pounds as frequently as needed to move objects; dexterity to write and manipulate computer keyboard and mouse; ability to hear and speak clearly; and ability to distinguish between colors on graphs and charts.

Employee may be required to visit construction jobsites which may expose the employee to dirt, dust, uneven surfaces, outdoor weather conditions and extreme temperatures.