Job description

Trusted by more startups around the world, AWS makes the power of cloud computing accessible for all by giving founders everywhere access to the same technology that powers the world's largest companies. With nearly two decades of experience supporting hundreds of thousands of startups, including 80% of unicorns, we democratize cloud computing to help founders bring their innovative ideas to life. We support founders at every stage of their journey, from initial onboarding and credit programs to AI-powered guidance and scale solutions. Data is central to how we do this: it helps us identify high-potential startups early, personalize the guidance we deliver, and prioritize where we can create the most value for founders and for AWS. We are seeking an Applied Science Manager to lead a team of applied scientists and analysts building the data and machine learning capabilities behind AWS Startups. You will own the science roadmap end-to-end, from the data foundation that unifies signals about founders, startups, and their products, through a portfolio of machine learning models, to the surfaces that put insights in the hands of the teams and products that serve startups. You will balance hands-on technical leadership with people management, setting the technical bar for your team while developing their careers. Key job responsibilities · Lead, coach, and grow a team of applied scientists, business intelligence engineers, and business analysts; hire and develop talent and set a high technical bar. · Own and prioritize the team's science roadmap across data foundation, model development, and the delivery of insights into products and internal tools. · Set technical direction for the team's machine learning models and data assets, balancing rapid experimentation with production quality, cost, and reliability. · Scope scientific projects, design and evaluate experiments, and ensure models are productionized and deliver measurable business impact. · Establish measurement, evaluation, and operational-excellence standards so model quality and impact are quantified and defensible. · Partner with product, engineering, design, and go-to-market teams to translate science into products and repeatable, scalable outcomes. · Communicate strategy, results, and trade-offs clearly to technical and non-technical leaders through written narratives and business reviews. · Foster a culture of scientific rigor, rapid experimentation, and operational excellence, and proactively identify and escalate risks with clear mitigation plans. About the team The AWS Startups team builds innovative products and platforms that support startup customers throughout their journey, from initial onboarding and credit programs to AI-powered guidance and scale solutions. Our portfolio serves hundreds of thousands of startup customers globally, and we partner with business development, field marketing, and solutions architecture teams worldwide. We are building the next generation of AI-native products that make world-class cloud expertise accessible to every founder. - 4+ years of applied research experience - 3+ years of scientists or machine learning engineers management experience - PhD, or Master's degree and 4+ years of applied research experience - Experience in several of the following areas: machine learning, statistics, deep learning, natural language processing, or information retrieval - Experience in one of the following programming languages: Java, Python, Ruby, Node.js, C#, or C - Experience building machine learning models or developing algorithms for business application - Experience with training and deploying machine learning systems to solve large-scale optimizations, or experience operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets - Experience in delivering results managing a business intelligence or analytics team, including employee development and performance management - Experience operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets, or experience with data infrastructures: relational analytic DBMS, Elastic-Search, and Big Data EMR/EC2/Glue/Lambda - Experience communicating results to senior leadership, or experience using complex financial models, KPIs, and data analysis to inform strategic business decisions and influence cross-functional stakeholders, with proven business impact (e.g., financial savings, operational improvements, or customer benefits) - Experience hiring, developing, and managing high-performing technical teams Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit amazon.jobs for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at amazon.jobs . USA, WA, Seattle - 183,800.00 - 248,700.00 USD annually

Requirements

Must-haves

Key job responsibilities
Lead, coach, and grow a team of applied scientists, business intelligence engineers, and business analysts; hire and develop talent and set a high technical bar.
Own and prioritize the team's science roadmap across data foundation, model development, and the delivery of insights into products and internal tools.
Set technical direction for the team's machine learning models and data assets, balancing rapid experimentation with production quality, cost, and reliability.
Scope scientific projects, design and evaluate experiments, and ensure models are productionized and deliver measurable business impact.
Establish measurement, evaluation, and operational-excellence standards so model quality and impact are quantified and defensible.
Partner with product, engineering, design, and go-to-market teams to translate science into products and repeatable, scalable outcomes.
Communicate strategy, results, and trade-offs clearly to technical and non-technical leaders through written narratives and business reviews.
Foster a culture of scientific rigor, rapid experimentation, and operational excellence, and proactively identify and escalate risks with clear mitigation plans.
About the team
4+ years of applied research experience
3+ years of scientists or machine learning engineers management experience
PhD, or Master's degree and 4+ years of applied research experience
Experience in several of the following areas: machine learning, statistics, deep learning, natural language processing, or information retrieval
Experience in one of the following programming languages: Java, Python, Ruby, Node.js, C#, or C
Experience building machine learning models or developing algorithms for business application
Experience in delivering results managing a business intelligence or analytics team, including employee development and performance management
Experience hiring, developing, and managing high-performing technical teams
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
USA, WA, Seattle - 183,800.00 - 248,700.00 USD annually

Nice-to-haves

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Application prep

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Keywords to mirror

awsaimachine learninggojavapythonnode.js

Platform: amazon
Effort: medium

Benefits

Benefits detected in the listing.

Health Insurance

Dental

Vision

401(K)

Paid Time Off

Parental Leave