Sr. Data Scientist, WWPS ProServe Data and Machine Learning

Overview

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 (AWS) Professional Services (Pro Serve) team is seeking a Data Scientist to join our team. You will work at the forefront of Machine Learning and AI, applying Generative AI algorithms to solve real-world problems with significant impact. In this role, you will work directly with customers to design, evangelize, implement, and scale AI/ML solutions that meet technical requirements and business objectives, driving customer success through their AI transformation journey.

As a Data Scientist within AWS Professional Services, you will architect complex, scalable, and secure machine learning solutions tailored to customer needs. You will help customers imagine and scope use cases that create the greatest value, develop statistical models and analytical frameworks, select and train models, and define paths to navigate technical or business challenges. You will assess data infrastructure, perform exploratory data analysis, develop proofs of concept, and propose strategies for implementing AI and generative AI solutions  will design experiments, research new algorithms, extract insights from complex datasets, and optimize risk, profitability, and customer experience.

AWS Pro Services is a global team helping customers realize their desired business outcomes when using the AWS Cloud. We work with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives and deliver focused guidance through our global specialty practices across various solutions, technologies, and industries.

• Designing and implementing complex, scalable, and secure AI/ML solutions on AWS tailored to customer needs, including statistical modeling, feature engineering, and selecting algorithms for specific use cases.
• Developing and deploying machine learning models and generative AI applications that solve real-world problems, conducting experiments, performing 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 ML and generative AI solutions.
• Providing technical guidance on applying AI/ML 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 advancements in AI/ML, emerging technologies, statistical methodologies, and approaches to leveraging diverse data sources for business impact.
• Sharing knowledge within the organization through mentoring, training, creating reusable AI/ML artifacts and analytical frameworks, and prototyping new technologies with team members.
• 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 experience involving data extraction, analysis, statistical modeling, and communication.
• 5+ years of experience with data querying languages (e.g., SQL), scripting languages (e.g., Python), or statistical/mathematical software (e.g., R, SAS, Matlab).
• Experience with statistical models (e.g., multinomial logistic regression).
• Current, active US Government Security Clearance of TS/SCI with Polygraph.
• 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, Hive).
• Experience applying quantitative analysis to solve business problems and making data-driven decisions.
• Experience in developing and deploying LLMs in production on GPUs, Neuron, TPU, or other AI acceleration hardware, or familiarity with ML and Large Language…