Senior Applied Scientist, Experience Analytics

Benefits

Parental leave

6 weeks From the posting source checked Jun 20, 2026

Non-birth-parent leave

6 weeks From the posting source checked Jun 20, 2026

Family-building benefits

• Fertility benefits: Offered From the posting source checked Jun 20, 2026
• Adoption assistance: Offered From the posting source checked Jun 20, 2026
• Surrogacy assistance: Not verified

Mental health support

Offered From the posting source checked Jun 20, 2026

Relocation assistance

Not verified

Childcare support

Offered From the posting source checked Jun 20, 2026

Learning budget

Not verified

Verification

Source-linked checked Jun 7, 2026

Salary

$167K-$226K From the posting source checked Jun 20, 2026

401(k) match

Reported from DOL Form 5500 industry filing (not employer-specific)

Was this benefit information wrong? Tell us.

Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

76% above the BLS role benchmark for data and ml aggregate.

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Data From the posting source checked Jun 20, 2026

Seniority

Senior From the posting source checked Jun 20, 2026

Schedule

Shift type

Not verified

Weekend work

Not verified

Company

Company stage

Public-company From the posting source checked Jun 20, 2026

Equity

Offered Verified - SEC 10-K source checked Jun 20, 2026

Application

Cover letter

Not verified

Assessment

Not verified

Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Senior Applied Scientist, Experience Analytics Seattle, Washington, USA AWS Experience Analytics (EXA) is seeking an Applied Scientist to join our team. EXA exists to turn customer understanding into products and intelligence that teams across AWS can use. We are building a unified customer lifecycle data platform, customer experience measurement frameworks, and segmentation systems, and the science that powers these products is well underway. What we need is someone who can add to our work in segmentation models, behavioural classifiers, and predictive frameworks - bringing both scientific depth and the production engineering skills to take models from notebook to production. You will bring your creative and learn and be curious mindset and work within the science team helping us ship faster across the full range of modelling and ML work and at greater scale. The problems are genuinely interesting. AWS customers are shifting from console-based building toward AI-augmented, agent-primary, and autonomous workflows. The signals that tell us who customers are, what they are trying to do, and where they struggle are changing fundamentally. There is more to model, more to explore, and more to build than the current team can get to - and that is where you come in. Key job responsibilities - Contribute to and extend the team's work in customer segmentation models, behavioral classification systems, and predictive frameworks - adding scientific depth and production engineering capability. - Build production ML infrastructure - offline training pipelines, online scoring systems, and monitoring. - Frame and tackle new modelling problems as

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