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Data Science Project Manager Jobs in Seattle, WA

The Director, Data Science provides strategic and operational leadership for MCG's Data Science ... Partner closely with Product Management, Engineering, Clinical, and Infrastructure teams to ...

Data Science Director Responsibilities: * Define the Data Science operating model across a ... Minimum Qualifications: * 10+ years of work experience managing analytics teams, working ...

... manage high performance, responsive team of data scientists and analysts that are able to not only keep up with but also pioneer in this space 3. Build and prototype analysis pipelines for the team ...

What You'll Bring * 5 or more years of relevant data science professional work experience; Master ... A proficiency in agile project planning and project management techniques. * Experience with Gen AI ...

Project Manager

Seattle, WA · On-site

$120K - $150K/yr

These roles will focus on delivering complex construction projects for life sciences ... As a Project Manager, you will leverage your 10+ years of construction and project management ...

These roles will focus on delivering complex construction projects for life sciences ... As a Project Manager, you will leverage your 10+ years of construction and project management ...

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Data Science Project Manager information

See Seattle, WA salary details

$19

$65

$91

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

As of Jul 17, 2026, the average hourly pay for data science project manager in Seattle, WA is $65.44, according to ZipRecruiter salary data. Most workers in this role earn between $56.63 and $76.59 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 Seattle, WA? For Data Science Project Manager jobs in Seattle, WA, the most frequently searched job titles are:
What job categories do people searching Data Science Project Manager jobs in Seattle, WA look for? The top searched job categories for Data Science Project Manager jobs in Seattle, WA are:
What cities near Seattle, WA are hiring for Data Science Project Manager jobs? Cities near Seattle, WA with the most Data Science Project Manager job openings:
Infographic showing various Data Science Project Manager job openings in Seattle, WA as of July 2026, with employment types broken down into 94% Full Time, and 6% Contract. Highlights an 80% In-person, 6% Hybrid, and 14% Remote job distribution, with an average salary of $136,125 per year, or $65.4 per hour.
Director, Data Science

$201K - $281K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 16 days ago


Job description

The Director, Data Science provides strategic and operational leadership for MCG's Data Science team responsible for developing advanced AI solutions that improve clinical decision support for payers and providers. This role leads a team of senior and staff-level data scientists in designing, developing, and deploying production-grade AI systems that leverage foundation models, proprietary clinical evidence, and emerging AI technologies to deliver measurable customer value.  

Working closely with Product, Engineering, Clinical, and executive leadership, the Director establishes technical direction, aligns AI research with business priorities, and ensures successful delivery of scalable AI capabilities. This leader balances technical depth with people leadership, fostering a high-performing, collaborative team while advancing MCG's AI strategy through innovation, operational excellence, and responsible adoption of emerging technologies. 

You Will:

  • Lead, coach, and develop a team of senior and staff data scientists, establishing clear priorities, fostering technical excellence, and supporting career growth. 
  • Define departmental priorities, technical direction, and execution plans that align AI initiatives with business objectives, product roadmaps, and customer needs. 
  • Ensure successful delivery of production-ready AI models, workflows, and services that meet quality, scalability, security, and performance expectations. 
  • Partner closely with Product Management, Engineering, Clinical, and Infrastructure teams to prioritize work, resolve dependencies, and deliver customer-focused AI solutions. 
  • Prototype and evaluate novel AI techniques, architectures, and agentic workflows that advance MCG's clinical AI capabilities and create competitive differentiation. 
  • Provide technical leadership in the design, evaluation, fine-tuning, and deployment of large language models and related AI technologies. 
  • Establish engineering and scientific best practices for experimentation, model evaluation, reproducibility, documentation, and operational excellence. 
  • Monitor emerging AI technologies, research, and industry trends to identify opportunities for innovation and continuous improvement. 
  • Communicate technical strategy, risks, tradeoffs, and progress to senior leadership and cross-functional stakeholders. 
  • Manage departmental planning, resource allocation, and execution to ensure delivery against organizational priorities. 
  • Foster a collaborative, inclusive, and high-performing team culture built on continuous learning and innovation. 
  • Champion the effective and responsible use of AI-assisted development tools and workflows across the team to improve productivity, quality, and delivery. 

What We're Looking For:

  • Master's degree or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, Data Science, or a related technical field, or equivalent practical experience. 
  • At least 10 years of experience developing machine learning, natural language processing, or AI solutions, including production deployment of large-scale systems. 
  • Demonstrated experience leading teams of senior and staff-level data scientists or machine learning engineers. 
  • Demonstrated success delivering AI-enabled products or services from concept through production. 
  • Deep understanding of large language model architectures, prompt engineering, retrieval-augmented generation (RAG), and model evaluation methodologies. 
  • Experience with fine-tuning techniques and modern approaches for adapting foundation models. 
  • Experience developing AI solutions in cloud environments such as AWS, Azure, or Google Cloud Platform. 
  • Strong proficiency in Python and modern machine learning frameworks such as PyTorch. 
  • Experience building scalable distributed AI systems and production ML pipelines. 
  • Excellent written and verbal communication skills with the ability to communicate complex technical concepts to diverse audiences. 

Preferred Qualifications

  • Experience developing AI solutions within healthcare or other highly regulated industries preferred. 
  • Experience with advanced agentic AI systems, autonomous workflows, and reasoning agents preferred. 
  • Experience with Kubernetes, Databricks, Flyte, or comparable cloud-native data science platforms preferred. 
  • Familiarity with retrieval-augmented generation (RAG), vector databases, and enterprise AI architectures preferred. 
  • Demonstrated ability to influence technical strategy across cross-functional teams and organizational boundaries. 
  • Strong analytical, strategic thinking, and problem-solving skills. 
  • Experience using AI-assisted software development tools (e.g., Claude Code, Cursor, GitHub Copilot, or similar) to improve engineering productivity and software quality preferred. 

Pay Range: $201,000 - $281,600

Other compensation: Bonus Eligible

Location Preference: Seattle-based talent preferred for this role

Perks & Benefits:

  Hybrid work

Travel expected 1-3 times per year for company-sponsored events

Medical, dental, vision, life, and disability insurance

401K retirement plan; flexible spending and health savings account

15 days of paid time off + additional front-loaded personal days

14 company-recognized holidays + paid volunteer days

up to 8 weeks of paid parental leave + 10 weeks of paid bonding leave

LGBTQ+ Health Services

Pet insurance

Check out more of our benefits here: https://www.mcg.com/about/careers/benefits/

All roles at MCG are expected to engage in occasional travel to participate in team or company-sponsored events for the purposes of connection and collaboration. 

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

Note on interviews: We may use AI tools to audio-record and transcribe interviews for note-taking purposes. These are used only by our hiring team and do not make decisions on their own. Let us know if you prefer an alternative.


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About MCG Health

Sourced by ZipRecruiter

MCG Health, part of the Hearst Health network, provides unbiased clinical guidance that gives healthcare organizations confidence in their patient-centered care decisions. Our artificial intelligence and technology solutions, infused with objective clinical expertise, enable our clients to prioritize and simplify their work. MCG’s world-class customer service ensures that our clients maximize the benefits of licensing MCG solutions – demonstrating improved financial and clinical outcomes.

Industry

Health care and social assistance

Company size

201 - 500 Employees

Headquarters location

Seattle, WA, US

Year founded

1990

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