📍
Boston, MA

Data Scientist, AWS Professional Services

2 years experience
Technology & Digital
Data / Analytics
Posted:
December 29, 2025

Amazon

Consumer goods marketplace and technology platform
76.7
Palpable Score
Apply >view company >

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.

We’re looking for 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.

Key job responsibilities

As an experienced Senior Data Scientist, you will be responsible for:

1. Lead end-to-end AI/ML and GenAI projects, from understanding business needs to data preparation, model development, solution deployment, and post-production monitoring

2. 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

3. 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

4. Create and deliver best practice recommendations, tutorials, blog posts, publications, sample code, and presentations tailored to technical, business, and executive stakeholders

5. Provide customer and market feedback to product and engineering teams to help define product direction

This is a customer-facing role with potential travel to customer sites as needed.

Basic Qualifications

- 2+ years of data scientist experience
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- 1+ years of guiding and coaching a group of researchers experience
- 1+ years of working with or evaluating AI systems experience
- 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
- Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
- Experience applying theoretical models in an applied environment

Preferred Qualifications

- Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
- Knowledge of machine learning concepts and their application to reasoning and problem-solving
- Experience in Python, Perl, or another scripting language
- Experience in a ML or data scientist role with a large technology company
- Experience in defining and creating benchmarks for assessing GenAI model performance
- Experience working on multi-team, cross-disciplinary projects
- Experience applying quantitative analysis to solve business problems and making data-driven business decisions
- Experience effectively communicating complex concepts through written and verbal communication

About the company

Amazon

Company overview
Amazon runs a wide set of consumer and enterprise businesses, including online retail, Prime Video and other subscription services, advertising, devices, and Amazon Web Services (AWS). Amazon also builds large-scale software and infrastructure for logistics, payments, and cloud computing, and hires across engineering, product, operations, corporate functions, and frontline roles. Amazon’s early-career hiring spans both office-based teams and operational sites, which means “entry-level” can look very different depending on the org.

Locations and presence

Amazon has major corporate hubs in Seattle and Arlington (HQ2) plus large engineering and operations sites across North America, EMEA, and Asia-Pacific. For many corporate roles, Amazon’s stated expectation has shifted to five days per week in-office for office-based employees (with exceptions depending on role and site).

Palpable Score

76.7
/ 100
Amazon is one of the most accessible early-career employers at scale, with recurring internships and graduate hiring across many disciplines and geographies. Amazon also provides unusually clear public information about interview mechanics and publishes pay ranges on a large share of roles, which supports informed decision-making. The biggest drag on outcomes is the combination of high-performance culture signals and recent corporate job cuts, which adds risk for early-career stability depending on team and org.
view full company profile >

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