Applied Scientist, Operations Research, Modeling and Optimization (MOP)

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

$143K-$193K 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

50% 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

Mid From the posting source checked Jun 20, 2026

Schedule

Shift type

Not verified

Weekend work

Not verified

Company

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

Applied Scientist, Operations Research, Modeling and Optimization (MOP) Bellevue, Washington, USA Amazon's Modeling and Optimization (MOP) team seeks motivated individual with strong analytical and algorithmic skills to optimize the global logistics network and its operations. Key job responsibilities - Enhance global logistics network efficiency through data-driven simulation and optimization - Reduce variable costs by improving network design, inventory placement, process and operational planning, and resource allocation - Optimize capital investment through strategic fixed asset deployment planning - Develop metrics to quantify business impact of implemented solutions A day in the life - Lead development of production-ready algorithms and scientific tools for under-the-roof (UTR) and network process analysis and optimization - Drive planning and execution decisions on operation timing and resource allocation to improve capacity, cost, and speed. - Manage customer interactions, promote science-based processes, and incorporate customer needs into tool improvements. - Partner with team members and customers to exercise judgment on appropriate analysis methods for various business requests. - Interact with and influence adjacent systems and tools, including those for long-term operating policies and daily capacity planning. - Blend scientific expertise with business acumen to deliver impactful solutions across the organization. Basic Qualifications: - 3+ years of building models for business application experience - PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience - Experience in patents or publications at top-tier peer-reviewed conferences or journals - Experience programming in Java, C++, Python or related language - Experience in any of the following areas:

Read the full description at www.amazon.jobs. FewerJobs shows a preview and links to the original posting.