How much do Data & Analytics jobs in Seattle, WA pay?

Based on 49 listings with disclosed salaries, most data & analytics jobs in Seattle, WA pay between $116k–$230k per year. Individual offers vary with seniority, company size, and specialization.

How many Data & Analytics jobs are open in Seattle, WA right now?

There are currently 56 open data & analytics positions in Seattle, WA listed on Clera. New openings are added daily as companies post roles.

Which companies are hiring for Data & Analytics roles in Seattle, WA?

Companies currently hiring include Amazon, Oracle, Meta, Nordstrom, Expedia Group, among others. Browse the listings above to see every active employer.

Are there remote or hybrid Data & Analytics jobs in Seattle, WA?

Yes — 18 of the 56 open data & analytics positions offer remote or hybrid work (1 remote, 17 hybrid).

How do I apply for Data & Analytics jobs in Seattle, WA?

Each listing links directly to the employer's application page. Apply early — fresh listings get the most recruiter attention in the first two weeks.

$116k–$230k Data & Analytics Jobs in Seattle, WA

As a Director of Software Engineering at JPMorgan Chase within the Agent Builder Platform team within the Corporate AI ML Technology Team, you will own the technical vision and delivery of the Agent SDK and the agentic systems it enables.

Job Responsibilities

Define and drive the technical vision and roadmap for the Agent SDK and long-running agentic workflows.
Set architectural direction for SDK components, including task orchestration, state management, checkpointing, and retry logic.
Champion data science rigor by establishing measurement, experimentation, and evaluation frameworks for agent performance.
Oversee the design and optimization of ML pipelines for training, fine-tuning, and inference of models powering agent intelligence.
Direct the instrumentation strategy for observability, feedback loops, and continuous improvement of autonomous agents.
Guide the adoption and extension of agent frameworks, supporting multi-step reasoning, tool use, and multi-agent coordination.
Build, mentor, and scale a high-performing team of ML engineers, data scientists, and platform engineers.
Collaborate with engineering, data science, product, and business stakeholders to align the team’s roadmap with enterprise AI strategy.
Serve as the primary technical point of contact for the Agent SDK platform, communicating complex trade-offs to diverse audiences.
Champion safe, responsible, and compliant agent systems by implementing guardrails and policy enforcement mechanisms.
Foster a collaborative environment where research insight translates into production impact.

Required Qualifications, Capabilities, and Skills

10 years of experience in machine learning engineering, applied data science, or ML platform development.
3 years of experience in a leadership role managing teams of engineers and/or data scientists.
Strong technical depth across the ML and data science stack, including ML frameworks (PyTorch, TensorFlow, JAX, scikit-learn) and LLM serving and fine-tuning toolchains.
Proven experience designing and delivering SDKs, platforms, or agent development kit, including API design and documentation strategy.
Expertise in distributed and long-running systems, including state machines, workflow orchestration, checkpointing, and fault-tolerant design.
Fluency in LLM-based agent architectures, prompt engineering, tool use, and multi-agent coordination patterns.
Demonstrated ability to craft and drive a technical vision that maximizes business impact and influences decision-making.
Proven ability to build, mentor, and retain senior technical talent and foster a collaborative team culture.
Strong foundation in experimental design, statistical analysis, and evaluation methodology.
Excellent communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences.
Experience integrating data science rigor and responsible AI practices into production systems.

Preferred Qualifications, Capabilities, and Skills

Experience building or contributing to open-source ML or agent frameworks such as LangChain, AutoGen, Haystack, or MLflow.
Background in ML evaluation and monitoring at scale, including drift detection, A/B testing, and automated regression testing.
Deep familiarity with multi-agent system design, including communication protocols, task delegation, and conflict resolution.
Experience overseeing AI workload deployment on managed ML platforms such as AWS SageMaker or Bedrock.
Background leading AI engineering in regulated or high-reliability environments, especially financial services or asset and wealth management.
Experience integrating user and stakeholder feedback loops into continuous model and system improvement processes.
Experience designing developer experience, writing technical documentation, and supporting internal developer adoption.

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans

Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we’re setting our businesses, clients, customers and employees up for success.

Job Responsibilities

Define and drive the technical vision and roadmap for the Agent SDK and long-running agentic workflows.
Set architectural direction for SDK components, including task orchestration, state management, checkpointing, and retry logic.
Champion data science rigor by establishing measurement, experimentation, and evaluation frameworks for agent performance.
Oversee the design and optimization of ML pipelines for training, fine-tuning, and inference of models powering agent intelligence.
Direct the instrumentation strategy for observability, feedback loops, and continuous improvement of autonomous agents.
Guide the adoption and extension of agent frameworks, supporting multi-step reasoning, tool use, and multi-agent coordination.
Build, mentor, and scale a high-performing team of ML engineers, data scientists, and platform engineers.
Collaborate with engineering, data science, product, and business stakeholders to align the team’s roadmap with enterprise AI strategy.
Serve as the primary technical point of contact for the Agent SDK platform, communicating complex trade-offs to diverse audiences.
Champion safe, responsible, and compliant agent systems by implementing guardrails and policy enforcement mechanisms.
Foster a collaborative environment where research insight translates into production impact.

Required Qualifications, Capabilities, and Skills

10 years of experience in machine learning engineering, applied data science, or ML platform development.
3 years of experience in a leadership role managing teams of engineers and/or data scientists.
Strong technical depth across the ML and data science stack, including ML frameworks (PyTorch, TensorFlow, JAX, scikit-learn) and LLM serving and fine-tuning toolchains.
Proven experience designing and delivering SDKs, platforms, or agent development kit, including API design and documentation strategy.
Expertise in distributed and long-running systems, including state machines, workflow orchestration, checkpointing, and fault-tolerant design.
Fluency in LLM-based agent architectures, prompt engineering, tool use, and multi-agent coordination patterns.
Demonstrated ability to craft and drive a technical vision that maximizes business impact and influences decision-making.
Proven ability to build, mentor, and retain senior technical talent and foster a collaborative team culture.
Strong foundation in experimental design, statistical analysis, and evaluation methodology.
Excellent communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences.
Experience integrating data science rigor and responsible AI practices into production systems.

Preferred Qualifications, Capabilities, and Skills

Experience building or contributing to open-source ML or agent frameworks such as LangChain, AutoGen, Haystack, or MLflow.
Background in ML evaluation and monitoring at scale, including drift detection, A/B testing, and automated regression testing.
Deep familiarity with multi-agent system design, including communication protocols, task delegation, and conflict resolution.
Experience overseeing AI workload deployment on managed ML platforms such as AWS SageMaker or Bedrock.
Background leading AI engineering in regulated or high-reliability environments, especially financial services or asset and wealth management.
Experience integrating user and stakeholder feedback loops into continuous model and system improvement processes.
Experience designing developer experience, writing technical documentation, and supporting internal developer adoption.

JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans

Data & Analytics Jobs in Seattle, WA (Now Hiring) — 56 open

Director of Software Engineering

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Principal AI Agent / ML Software Engineer (OCI)

Member of Technical Staff — RL Research (New PhD Grad)

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internal audit analysis manager, IT Audit

Senior Software Engineer - Seattle, WA

Frequently asked questions

How much do Data & Analytics jobs in Seattle, WA pay?

How many Data & Analytics jobs are open in Seattle, WA right now?

Which companies are hiring for Data & Analytics roles in Seattle, WA?

Are there remote or hybrid Data & Analytics jobs in Seattle, WA?

How do I apply for Data & Analytics jobs in Seattle, WA?

Data & Analytics jobs in other cities

Other jobs in Seattle, WA

Director of Software Engineering

Job description

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Data & Analytics Jobs in Seattle, WA (Now Hiring) — 56 open

Director of Software Engineering

Senior Financial Analyst, AWS SMGS Ops

UX Researcher, Mixed Methods

Principal Software Engineer, Database Services

Data Scientist, AWS Support Capacity Planning

Engineering Manager, HADR

Bluebeam Project lead

Marketing Manager - Pacific Northwest

Senior Data Specialist - Oncology

Financial Analyst, Connected Warfare

Marketing Manager - Pacific Northwest

Engineering Leader, Data Engineering

Program Manager, Commercial

Nuance Research Fellow

Senior Principal AI Agent / ML Engineer (OCI)

Principal AI Agent / ML Software Engineer (OCI)

Member of Technical Staff — RL Research (New PhD Grad)

Member of Technical Staff — Model Optimization and Inference (New Grad)

internal audit analysis manager, IT Audit

Senior Software Engineer - Seattle, WA

Frequently asked questions

How much do Data & Analytics jobs in Seattle, WA pay?

How many Data & Analytics jobs are open in Seattle, WA right now?

Which companies are hiring for Data & Analytics roles in Seattle, WA?

Are there remote or hybrid Data & Analytics jobs in Seattle, WA?

How do I apply for Data & Analytics jobs in Seattle, WA?

Data & Analytics jobs in other cities

Other jobs in Seattle, WA

Director of Software Engineering

Job description

Tools

Explore

Company