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Data Science Product Manager Jobs in Redmond, WA

MCG Health

Director, Data Science

Seattle, WA

$201K - $281K/yr

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 ...

Anthropic

Data Scientist, Product

Seattle, WA · On-site

About the role As part of our growing Data Science and Analytics team, you will play an ... Deep dive into product and user data to derive actionable insights and size opportunities to ...

New

Meta

Data Science Director (IC)

Bellevue, WA

$253K/yr

... measurement, and data product management, and will be enthusiastic about cutting-edge AI ... Data Science Director (IC) Responsibilities: * Collaborate with Engineering, Product, and cross ...

Chewy

Director, Data Science

Bellevue, WA · On-site

... management - orchestrating Chewy's onsite and offsite Ads portfolio for optimal, balanced ... Partner with Product and Engineering to ship production systems that improve shopper relevance ...

Chewy

Director, Data Science

Bellevue, WA

... management -- orchestrating Chewy's onsite and offsite Ads portfolio for optimal, balanced ... Partner with Product and Engineering to ship production systems that improve shopper relevance ...

Opendoor

Data Scientist

Seattle, WA · On-site

$169K - $233K/yr

Every pricing signal we generate directly impacts how we value homes, how we manage risk, and how ... science, product analytics, or a similar quantitative role. #LI-RO The pay range for this role is ...

Databricks

Sr. Product Manager, Data Governance

Seattle, WA · On-site

$144K - $190K/yr

The Sr Product Manager for Unity Catalog will coordinate product activities from vision to ... Science & Engineering, Data Warehousing, etc.) to easily add new workload-specific governance ...

OpenDoor

Data Scientist

Seattle, WA · On-site

$169.60 - $233.20/hr

Every pricing signal we generate directly impacts how we value homes, how we manage risk, and how ... data science, product analytics, or a similar quantitative role. The pay range for this role is ...

Chewy

Senior Technical Product Manager

Bellevue, WA

$141K - $225K/yr

Coordinate across engineering, data science, product, and operations teams to deliver scalable and reliable solutions * Manage cross-team dependencies, risks, and tradeoffs , proactively identifying ...

MCG Health

Director, Data Science

Seattle, WA · On-site

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 ...

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All JobsData Science Product JobsData Science Product Manager JobsData Science Product Manager Jobs in Redmond, WA

Data Science Product Manager information

See Redmond, WA salary details

$57.7K

$178.5K

$220.6K

How much do data science product manager jobs pay per year?

As of Aug 26, 2026, the average yearly pay for data science product manager in Redmond, WA is $178,525.00, according to ZipRecruiter salary data. Most workers in this role earn between $157,900.00 and $220,600.00 per year, depending on experience, location, and employer.

What is a Data Science Product Manager?

A Data Science Product Manager is a professional who bridges the gap between data science teams and business objectives by guiding the development of data-driven products. They work closely with data scientists, engineers, and stakeholders to define product vision, prioritize features, and ensure successful product delivery. Their role involves understanding both the technical aspects of machine learning and analytics as well as user needs and business strategy. This ensures that data-powered products are effective, user-focused, and aligned with organizational goals.

How does a Data Science Product Manager typically collaborate with data scientists and engineers during a product lifecycle?

A Data Science Product Manager plays a crucial role in bridging the gap between business objectives and technical teams. Throughout the product lifecycle, they work closely with data scientists to define project goals, prioritize features, and translate business needs into actionable data-driven solutions. They also coordinate with engineers to ensure the seamless integration of machine learning models into products, address technical constraints, and facilitate communication between cross-functional teams. This collaborative approach ensures that data science initiatives are both technically feasible and aligned with overall business strategy.

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

To thrive as a Data Science Product Manager, you need a strong background in product management, data analytics, and a foundational understanding of machine learning, often supported by a degree in a technical or quantitative field. Familiarity with tools like SQL, Python, JIRA, and knowledge of data platforms and agile methodologies is typically required. Excellent communication, strategic thinking, and the ability to bridge technical and non-technical teams are vital soft skills. These competencies ensure successful product development, effective stakeholder alignment, and the delivery of impactful data-driven solutions.

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

AspectData Science Product ManagerData Analyst
Required credentialsBackground in data science, product management, or related fields; often requires experience with machine learning and data-driven product developmentTypically holds a degree in statistics, mathematics, or business; skills in data visualization and basic analytics
Work environmentCollaborates with product teams, data scientists, engineers; focuses on developing data products and strategiesWorks with business units to interpret data, generate reports, and support decision-making
Employer and industry usageUsed in tech companies, e-commerce, and organizations developing data-driven productsCommon across finance, marketing, healthcare, and business intelligence roles

The main difference is that Data Science Product Managers oversee the development of data products and strategies, requiring a blend of product management and data science skills. Data Analysts focus on interpreting data and generating insights to support business decisions. Both roles are essential in data-driven organizations but serve different functions within the data ecosystem.

What are popular job titles related to Data Science Product Manager jobs in Redmond, WA?

For Data Science Product Manager jobs in Redmond, WA, the most frequently searched job titles are:

What job categories do people searching Data Science Product Manager jobs in Redmond, WA look for?

The top searched job categories for Data Science Product Manager jobs in Redmond, WA are:

What cities near Redmond, WA are hiring for Data Science Product Manager jobs?

Cities near Redmond, WA with the most Data Science Product Manager job openings:

Data Science Product Manager jobs near you
Infographic showing various Data Science Product Manager job openings in Redmond, WA as of August 2026, with employment types broken down into 87% Full Time, 11% Part Time, and 2% Contract. Highlights an 81% Physical, 2% Hybrid, and 17% Remote job distribution, with an average salary of $178,525 per year, or $85.8 per hour.

Senior Product Manager, AI & Data Science Products

Crunchbase

Seattle, WA • On-site, Remote

$144K - $190K/yr

Full-time

Posted 15 days ago

Job description

About Crunchbase
Crunchbase is a predictive solution that provides intelligence on private companies, powered by the unique combination of live private company data, AI, and market activity from over 80 million users. We predict private market movements that matter to help investors, dealmakers, and analysts make the right decisions.
We are committed to fostering a positive, diverse, and inclusive culture by hiring for potential and embracing individuals with diverse perspectives, backgrounds, experiences, and skill sets. We value transparency and openness, believing that an inclusive environment strengthens our teams and enhances our products.
About the Role
The Senior Product Manager, AI & Data Science Products owns Crunchbase's customer-facing AI data layer: proprietary data and intelligence generated from foundational data using AI and machine learning.
The primary charter is to identify high-value opportunities for new model-derived data, validate their value with customers, and take successful products from experimentation through scaled adoption.
Success is measured by three outcomes:
  • New differentiated data: Create proprietary intelligence that Crunchbase could not practically produce through collection alone.
  • Higher customer value: Help customers discover, understand, evaluate, and prioritize their private market jobs more effectively.
  • Revenue and adoption: Turn valuable AI data into measurable usage, retention, expansion, and monetization opportunities.
What You'll Do
AI & Data Science Product Strategy
  • Own the strategy and roadmap for Crunchbase's customer-facing AI data layer.
  • Identify high-value opportunities for new predictions, classifications, signals, and insights that improve customer decisions.
  • Build a differentiated portfolio of AI data products rather than isolated AI features.
  • Partner with Foundational Data to determine when customer needs are best addressed through collected, acquired, inferred, predicted, or generated data.
Customer Discovery & Product Development
  • Work directly with customers to identify where new or better data can materially improve their workflows and decisions.
  • Rapidly test new AI data concepts, validate customer value, and scale successful products.
  • Define how model-derived data, including confidence and uncertainty, should be presented to customers.
  • Partner with Design, Engineering, and Data Science to deliver AI data across Crunchbase products, APIs, MCP, and data delivery experiences.
Quality & Product Economics
  • Define quality standards and evaluation frameworks for model-derived data in partnership with Data Science.
  • Determine when an AI data product is sufficiently reliable for scaled customer use.
  • Balance customer value, coverage, accuracy, freshness, and generation cost.
  • Monitor product and data performance and continuously improve quality based on customer feedback and observed outcomes.
Adoption & Monetization
  • Drive adoption of AI data products across Crunchbase's customer experiences and distribution channels.
  • Partner with Go-to-Market on positioning, customer education, and launch strategy.
  • Partner with Pricing and Packaging and Sales to identify monetization opportunities.
  • Measure adoption, retention, expansion, revenue, and customer outcomes to determine which products to scale, improve, or retire.
What We're Looking For
  • Strong product judgment across customer discovery, strategy, prioritization, experimentation, and tradeoffs.
  • Strong understanding of data products and how customers derive value from proprietary data and insights.
  • Practical understanding of modern machine learning and AI capabilities and limitations.
  • Working knowledge of applied data science and machine learning.
  • Ability to translate product requirements for Data Science and Engineering teams.
  • Familiarity with model evaluation concepts such as precision, recall, confidence, and model drift.
  • Ability to reason about probabilistic and imperfect data and define appropriate quality thresholds.
  • Strong analytical skills and ability to balance customer value, quality, coverage, cost, and speed.
  • Excellent customer discovery, communication, and cross-functional leadership skills.
Education and Experience
  • 3+ years of Product Management, Data Product Management, AI/ML Product Management, or comparable experience.
  • Experience owning customer-facing data science products from problem definition through launch and ongoing monitoring.
  • Experience partnering closely with Data Science and Engineering teams.
  • Demonstrated experience taking products from customer discovery and experimentation through scaled adoption.
  • Ability to define quality criteria that reflect customer needs and make informed quality and coverage tradeoffs.
  • Experience with B2B SaaS, data products, APIs, intelligence platforms, or commercializing differentiated data preferred.
Success in This Role Looks Like
  • Crunchbase launches differentiated AI data products that customers value and competitors cannot easily replicate.
  • AI creates valuable intelligence and coverage that would be impractical to produce through traditional data collection alone.
  • Customers adopt these products because they improve real workflows and decisions.
  • AI data products contribute measurably to adoption, retention, expansion, and revenue while meeting appropriate quality and trust standards.
Non-Goals
  • This is not an internal AI tooling or general AI feature role.
  • This is not ownership of foundational data collection, sourcing, or operations.
  • This is not ML research or data generation for its own sake. AI data must solve meaningful customer problems and create measurable value.
Interview Process
We use a structured interview process so every conversation has a distinct purpose and candidates are evaluated consistently against role-relevant evidence.
  1. Recruiter Prescreen - qualification and mutual fit. Confirm role basics, motivation, logistics, compensation alignment, and candidate priorities.
  2. Interview Round 1 - hiring-manager evidence interview. Evaluate the capabilities most predictive of success using consistent behavioral questions and anchored scoring.
  3. Interview Round 2 - work sample or functional deep dive. Explore the role's most important on-the-job capabilities through a realistic, time-bounded discussion or exercise.
  4. Final Round - decision-gap interview. Assess any unresolved evidence required for a confident decision, such as cross-functional collaboration, judgment, leadership, or values in practice.

Department Product Role Product Management Locations Multiple locations Remote status Fully Remote Employment type Full-time

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