Senior Data Scientist, AWS Professional Services

Amazon•Boston, MA

38d

About The Position

Are you looking to work at the forefront of Machine Learning (ML) and Artificial Intelligence (AI)? Would you be excited to apply AI algorithms to solve real world problems with significant impact? The Amazon Web Services Professional Services (ProServe) team is seeking a skilled Senior Data Scientist to help customers implement AI/ML solutions and realize transformational business opportunities. This is a team of scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of AI. The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and train and fine-tune the right models, define paths to navigate technical or business challenges, develop scalable solutions and applications, and launch them in production. The team provides guidance and implements best practices for applying AI responsibly and cost efficiently. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We’re looking for Senior Data Scientists capable of using AI/ML and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.

Requirements

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
4+ years of data scientist experience
Experience with statistical models e.g. multinomial logistic regression

Nice To Haves

2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
Experience managing data pipelines
Experience as a leader and mentor on a data science team

Responsibilities

Lead end-to-end AI/ML and GenAI projects, from understanding business needs to data preparation, model development, solution deployment, and post-production monitoring
Collaborate with AI/ML scientists, engineers, and architects to research, design, develop, and evaluate AI algorithms and build ML systems and operations (MLOps) using AWS services to address real-world challenges
Interact with customers directly to understand the business challenges, deliver briefing and deep dive sessions to customers and guide them on adoption patterns and paths to production
Create and deliver best practice recommendations, tutorials, blog posts, publications, sample code, and presentations tailored to technical, business, and executive stakeholders
Provide customer and market feedback to product and engineering teams to help define product direction