Sr. Data Scientist, WWPS ProServe Data and Machine Learning

ID: 7053

Type: Full-time

Category: Others

Company Name: Amazon Web Services, Inc.

Location: USA, VA, Arlington; USA, VA, Herndon - Herndon - United States

Salary: 159,200.00 - 215,300.00 USD annually

Job Description

This position requires that the candidate selected be a US Citizen and must currently possess and maintain an active TS/SCI security clearance with polygraph.

The Amazon Web Services Professional Services (ProServe) team is seeking a skilled Data Scientist to join our team at Amazon Web Services (AWS). Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? In this role, you'll work directly with customers to design, evangelize, implement, and scale AI/ML solutions that meet their technical requirements and business objectives. You'll be a key player in driving customer success through their AI transformation journey, providing deep expertise in data science, machine learning, generative AI, and best practices throughout the project lifecycle.

As a Data Scientist within the AWS Professional Services organization, you will be proficient in architecting complex, scalable, and secure machine learning solutions tailored to meet the specific needs of each customer. You'll help customers imagine and scope the use cases that will create the greatest value for their businesses, develop statistical models and analytical frameworks, select and train the right models, and define paths to navigate technical or business challenges. Working closely with stakeholders, you'll assess current data infrastructure, perform exploratory data analysis, develop proof-of-concepts, and propose effective strategies for implementing AI and generative AI solutions at scale. You will design and run experiments, research new algorithms, extract insights from complex datasets, and find new ways of optimizing risk, profitability, and customer experience.

The AWS Professional Services organization is a global team of experts that help customers realize their desired business outcomes when using the AWS Cloud. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives. Our team provides assistance through a collection of offerings which help customers achieve specific outcomes related to enterprise cloud adoption. We also deliver focused guidance through our global specialty practices, which cover a variety of solutions, technologies, and industries.

Key job responsibilities
- Designing and implementing complex, scalable, and secure AI/ML solutions on AWS tailored to customer needs, including developing statistical models, performing feature engineering, and selecting appropriate algorithms for specific use cases
- Developing and deploying machine learning models and generative AI applications that solve real-world business problems, conducting experiments, performing rigorous statistical analysis, and optimizing for performance at scale
- Collaborating with customer stakeholders to identify high-value AI/ML use cases, gather requirements, analyze data quality and availability, and propose effective strategies for implementing machine learning and generative AI solutions
- Providing technical guidance on applying AI, machine learning, and generative AI responsibly and cost-efficiently, performing model validation and interpretation, troubleshooting throughout project delivery, and ensuring adherence to best practices
- Acting as a trusted advisor to customers on the latest advancements in AI/ML, emerging technologies, statistical methodologies, and innovative approaches to leveraging diverse data sources for maximum business impact
- Sharing knowledge within the organization through mentoring, training, creating reusable AI/ML artifacts and analytical frameworks, and working with team members to prototype new technologies and evaluate technical feasibility

Basic Qualifications

- Bachelor's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
- 5+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience
- 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- Experience with statistical models e.g. multinomial logistic regression
- Current, active US Government Security Clearance of TS/SCI with Polygraph

Preferred Qualifications

- Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
- Experience as a leader and mentor on a data science team
- Experience in data applications using large scale distributed systems (e.g., EMR, Spark, Elasticsearch, Hadoop, Pig, and Hive)
- Experience applying quantitative analysis to solve business problems and making data-driven business decisions
- Experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware, or experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution

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 https://amazon.jobs/content/en/how-we-hire/accommodations 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 https://amazon.jobs/en/benefits.

USA, VA, Arlington - 159,200.00 - 215,300.00 USD annually
USA, VA, Herndon - 159,200.00 - 215,300.00 USD annually

Company Information

Company Name: Amazon Web Services, Inc.

Company Website: https://aws.amazon.com

Company Address: 410 Terry Ave N, Seattle, WA 98109-5210, United States

Amazon Web Services, Inc. (AWS) is the cloud computing and infrastructure arm of Amazon.com, Inc., offering a broad and evolving portfolio of on-demand cloud services, platform services, and infrastructure products for organizations of all sizes. Founded to provide scalable, reliable, and cost-effective computing resources over the internet, AWS enables customers to deploy and run applications and services without the need to build and maintain physical datacenters. The company’s public materials describe it as a provider of on-demand cloud computing platforms and APIs to individuals, companies, and governments, supplying infrastructure and higher-level services that accelerate application development, data processing, storage, and global delivery. Core business activities: AWS’s primary business is the design, operation, and delivery of cloud-based computing resources and managed services. That includes offering virtualized compute capacity, object and block storage, database engines (managed relational and NoSQL), networking primitives, identity and access management, security and compliance tooling, analytics and big-data processing stacks, machine learning and AI services, developer and application deployment tools, serverless computing, container orchestration services, content delivery, and Internet of Things (IoT) connectivity. AWS also provides enterprise-focused offerings such as hybrid cloud solutions, migration services to assist organizations in moving on-premises workloads to the cloud, managed operations and support plans, professional services, and training and certification programs for IT professionals. Main products and services: AWS’s product set spans foundational infrastructure to highly managed, domain-specific offerings. Key foundational services include Amazon Elastic Compute Cloud (EC2) for virtual servers, Amazon Simple Storage Service (S3) for scalable object storage, and Amazon Virtual Private Cloud (VPC) for isolated networking. Managed database and data services include Amazon Relational Database Service (RDS), Amazon Aurora (a high-performance relational database), Amazon DynamoDB (a fully managed NoSQL database), Amazon Redshift (a petabyte-scale data warehouse), and Amazon ElastiCache (in-memory caching). For compute modernization, AWS provides AWS Lambda (serverless compute), Amazon Elastic Kubernetes Service (EKS), and Amazon Elastic Container Service (ECS). AWS’s advanced and specialized services include Amazon SageMaker for building, training, and deploying machine learning models; Amazon Rekognition for computer vision; Amazon Comprehend for natural language processing; AWS Glue and AWS Data Pipeline for ETL and data integration; and AWS IoT Core for connecting and managing Internet of Things devices. Application delivery and developer tooling include Amazon API Gateway, AWS CloudFormation for infrastructure as code, AWS CodePipeline and CodeBuild for CI/CD, and Amazon CloudFront for content delivery across a global edge network. The AWS Marketplace and AWS Partner Network (APN) provide channels for third-party software, consulting partners, and managed service providers to offer products and services that run on or integrate with AWS. Infrastructure, delivery model, and pricing: AWS operates a global infrastructure composed of multiple geographic Regions, each containing multiple Availability Zones—physically separate data center locations engineered for fault isolation and high availability. This global footprint supports data residency, low-latency delivery, and resilience for customers deploying distributed systems. AWS’s commercial model emphasizes flexible consumption and cost control: customers commonly choose pay-as-you-go billing for on-demand resources, with options for reserved capacity, savings plans, and spot instances to reduce costs for predictable or interruptible workloads. Support tiers and managed services are available at varying cost and service-level commitments. Security, compliance, and governance: AWS provides a suite of security and identity services—such as AWS Identity and Access Management (IAM), AWS Key Management Service (KMS), AWS CloudTrail, and AWS Config—to help customers secure environments, manage access, encrypt data, and demonstrate compliance. AWS documents participation in standard industry compliance frameworks and certifications, and publishes detailed security and compliance resources to help customers meet regulatory obligations. Customer segments and use cases: AWS serves a broad range of customers that include startups, established enterprises, public sector organizations, educational institutions, and independent software vendors. Common use cases include web and mobile application hosting, data analytics and warehousing, machine learning and AI workloads, backup and disaster recovery, IoT deployments, gaming infrastructure, and enterprise application modernization. AWS emphasizes scalability, elasticity, and rapid provisioning to support development velocity and business agility. Ecosystem, training, and partner network: AWS supports a large ecosystem of technology and consulting partners that build, certify, and deliver solutions on the platform. The company offers official training, certifications, and documentation to help developers, architects, and IT professionals gain proficiency on its services. AWS Marketplace and partner programs provide channels for third-party software procurement and professional services. Business model and positioning: AWS generates revenue principally through consumption-based fees for cloud services and through related professional services and support offerings. It competes in the global cloud infrastructure market with other major cloud providers by focusing on breadth of services, global infrastructure, developer tooling, partner ecosystem, and continuous release of new managed services. AWS positions itself as an enabler for digital transformation by reducing the capital and operational burden of running infrastructure, allowing customers to focus on application development and business innovation. For additional, up-to-date, and authoritative information on product details, global infrastructure, security programs, and service announcements, AWS’s official website and documentation pages provide comprehensive resources and customer-facing materials.

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