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Data Science Project Manager Jobs in Ashburn, VA

Data Scientist

Springfield, VA · On-site

$92.30 - $166.85/hr

Experience managing data science projects, data mining, spatio-temporal analysis. Docker/Jupyter Hub/GIT. * Experience with "big data" processing and analytics (Databricks/Apache Spark or similar)

About the Role This is a senior leadership role on the Global Product Management Data Science team managing the Client Experience Digital Platform - the central hub where clients interact with ...

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 ...

New

Ability to lead multi-disciplinary teams to complete complex data science projects.. * Experience with AWS or similar cloud provider. * Demonstrated experience in solving problems with structured and ...

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 ...

New

Project Manager

Potomac, MD · On-site

$70K - $120K/yr

NACI AMDEX.ai The Art of Data Science We are a seasoned Full-spectrum data solutions firm. We ... The Project Manager shall be responsible for leading and managing projects from initiation to ...

The role involves applying data science techniques, particularly in cybersecurity solutions, to ... equivalent project management process Company : VTG delivers force modernization and digital ...

Showing results 41-60

Data Science Project Manager information

See Ashburn, VA salary details

$17

$58

$82

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

As of Aug 20, 2026, the average hourly pay for data science project manager in Ashburn, VA is $58.81, according to ZipRecruiter salary data. Most workers in this role earn between $50.87 and $68.85 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 Ashburn, VA?

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

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

The top searched job categories for Data Science Project Manager jobs in Ashburn, VA are:

What cities near Ashburn, VA are hiring for Data Science Project Manager jobs?

Cities near Ashburn, VA with the most Data Science Project Manager job openings:

Infographic showing various Data Science Project Manager job openings in Ashburn, VA as of August 2026, with employment types broken down into 80% Full Time, and 20% Part Time. Highlights an 100% In-person job distribution, with an average salary of $122,321 per year, or $58.8 per hour.

Senior Data Scientist - Fulltime

Rootshell Enterprise Technologies, Inc.

Arlington, VA • On-site

Full-time

Re-posted 4 days ago


Job description

Position: Senior Data Scientist
Location: Arlington, VA (5 days on site)
Locals Preferred
Top 3 Skills:
8 years of data science experience Azure, Data Bricks, PySpark
Be able to communicate directly with business stakeholders
Job Description:
The Senior Data Scientist is responsible for developing and maintaining data analytics solutions and machine learning algorithms. As a senior role, the expectations are to mentor junior data scientists, further develop the data science lifecycle and best practices, and contribute to strategic discussions. The measures of an ideal candidate include communication skills, technical proficiency, collaboration, mentorship, strategic-thinking, and willingness to learn new things. This new position will be based in our Arlington, VA headquarters and report to the Director of Business Intelligence. This position is structured within IT under the Vice President of Applications.
The position will be located in Arlington, VA.
Key Responsibilities and Essential Duties:
  • Develop solutions to business problems using the data science life cycle.
  • Develop and maintain data analytics solutions and machine learning algorithms
  • Develop comprehensive project plans for implementing data science projects including solution architectures, resourcing, and dependencies.
  • Use predictive modeling and classification techniques to improve LNG production efficiency and mitigate safety or downtime risks.
  • Mine and analyze data from a data lake or data warehouse to drive optimization.
  • Work with stakeholders to identify opportunities to leverage data science to drive business solutions.
  • Understand where key decisions are needed and communicate options for solving business problems with stakeholders.
  • Provide ETL requirements to data engineers to effectively curate files for data analytics.
  • Document data science algorithms for maintainability.
  • Work with IT leadership to further define the data science life cycle and enhance the data science technology stack and architecture.
  • Design data architecture for future platform growth including data warehousing, machine learning, streaming analytics, and data visualization.
  • Assist in testing, governance, data quality, training, and documentation efforts.
  • Mentor junior data scientists and data analysts.
  • Actively engage in business stakeholder requirement workshops to understand, interpret, and translate requirements into effective technical solutions.

Job Qualifications
  • 8+ Years of practical data science/data analytics experience.
  • Bachelor's degree in computer science, Data Analytics, Engineering, Mathematics, Business, or related field of study.
  • Knowledge in cloud data analytics solutions, managing, developing, and maintaining machine learning solutions.
  • Fundamental skills in data processing languages such as SQL, Python, or Scala.
  • Knowledge in building data science solutions using cloud data services.
  • Ability to self-manage and make your own decisions.
  • Strong presentation skills to effectively communicate results of analytics to stakeholders.
  • Strong documentations skills.
  • Excellent interpersonal and communications skills, with strong critical thinking and attention to detail.
  • Strong work ethic with ability to effectively prioritize, meet deadlines, adapt to changing priorities and business needs, and succeed in a fast-paced environment.
  • Excellent attention to detail and the ability to efficiently summarize and prioritize information.
  • Preferred Qualifications
  • Experience with Azure infrastructure especially Azure Data Lake and Azure Data Factory.
  • Experience using Databricks for machine learning algorithm development
  • Experience in coding languages primarily PySpark, Python,and SQL.
  • Experience in agile development and sprint planning.
  • Experience utilizing DevOps
  • Experience working with streaming datasets/IoT.
  • Strong technical writing skills.