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Data Science Project Manager Jobs in Dallas, TX (NOW HIRING)

Summary This role manages a team of data scientists responsible for a portfolio of diagnostic, predictive, and prescriptive analytics projects to support data-driven business decision making in ...

The Manager - Data Science role is essential for determining effective CRM tactics that drive ... Responsibilities : • Strategic Thought Partnership • Design and execute analytics projects to ...

Manager - Data Science

Irving, TX · On-site

$100 - $130/hr

Design and execute analytics projects to quantify impact from various marketing campaigns* Identify ... Manage a team of data scientists* Mentor analysts regarding analytics best practices, methodologies ...

Lead data science projects in close collaboration with IT, Data Engineering, Application development, PMO and business leaders to deliver high-value business capabilities * Architect and build ...

Lead data science projects in close collaboration with IT, Data Engineering, Application development, PMO and business leaders to deliver high-value business capabilities * Architect and build ...

Project Manager With Data Analytics

Dallas, TX · On-site

$51.25 - $69.25/hr

Minimum 8 - 10 years of overall experience in Analytics/Data Science space with 5 - 6 years working as Project Managing projects in this area. Working knowledge of data mining principles: predictive ...

New

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

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Data Science Project Manager information

See Dallas, TX salary details

$15

$52

$73

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

As of Aug 23, 2026, the average hourly pay for data science project manager in Dallas, TX is $52.71, according to ZipRecruiter salary data. Most workers in this role earn between $45.62 and $61.68 per hour, depending on experience, location, and employer.

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.

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 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.

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 popular job titles related to Data Science Project Manager jobs in Dallas, TX?

For Data Science Project Manager jobs in Dallas, TX, the most frequently searched job titles are:

What job categories do people searching Data Science Project Manager jobs in Dallas, TX look for?

The top searched job categories for Data Science Project Manager jobs in Dallas, TX are:

What cities near Dallas, TX are hiring for Data Science Project Manager jobs?

Cities near Dallas, TX with the most Data Science Project Manager job openings:

Infographic showing various Data Science Project Manager job openings in Dallas, TX as of August 2026, with employment types broken down into 87% Full Time, 11% Part Time, and 2% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $109,637 per year, or $52.7 per hour.

Technical Project Manager Data Engineering Data Science

Plugins Inc

Dallas, TX • On-site

$51.50 - $69.50/hr

Other

Posted 27 days ago


Job description

Technical Project Manager | Data Engineering & Data Science
Location: Dallas, TX  Hybrid (Onsite + Remote)
Employment Type: Full Time / Contract (W2)
Duration: 12+ Months (Ongoing)
Cloud Environment: Amazon Web Services (AWS)
Team Structure: US Onsite Teams and Offshore GCC Teams
We are seeking an experienced Technical Project Manager with strong expertise in Data Engineering and Data Science programs to lead enterprise initiatives within a large commercial airline environment.
In this role, you will coordinate project delivery between onsite leadership in the United States and offshore Global Capability Center (GCC) teams, driving AWS-based Data Engineering, Analytics, and Machine Learning initiatives from planning through successful delivery.
Required Qualifications
Technical Skills
* Experience managing Data Engineering and/or Data Science projects
Strong understanding of AWS data services: Amazon S3 • AWS Glue • Amazon Redshift • Amazon EMR • Amazon Athena • Amazon SageMaker • AWS Lambda • AWS Step Functions
* Knowledge of ETL/ELT frameworks and modern data pipeline architecture
* Familiarity with Machine Learning lifecycle management
* Experience with Agile delivery methodologies (Scrum or SAFe)
* Experience using Jira, Confluence, or similar project management tools
* Understanding of cloud security, data governance, and data quality best practices

Project Management

* Experience managing complex enterprise technology programs
* Experience coordinating onsite and offshore GCC teams
* Strong skills in project planning, dependency management, risk management, and stakeholder communication
* Ability to communicate technical concepts effectively to executive leadership
Professional Skills
* Excellent verbal and written communication
* Strong organizational and planning abilities
* Ability to manage multiple priorities in a fast-paced environment
* Comfortable working with cross-functional and multicultural teams
Key Responsibilities
Project Delivery
* Lead end-to-end delivery of Data Engineering and Data Science initiatives
* Define project scope, timelines, milestones, and success metrics
* Manage project plans, RAID logs, risk registers, and executive status reporting
* Lead Agile ceremonies including sprint planning, stand-ups, reviews, and retrospectives
Offshore Team Coordination
* Serve as the primary liaison between onsite stakeholders and offshore GCC teams
* Coordinate work across multiple time zones
* Manage resource planning, priorities, escalations, and delivery governance
* Ensure transparency and accountability across distributed teams