Data Scientist, Builder Insights

- 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
- Experience applying theoretical models in an applied environment
- Experience in Python, Perl, or another scripting language
- Experience in a ML or data scientist role with a large technology company
- Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $125,500/year in our lowest geographic market up to $212,800/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
Are you excited about the prospect of making it easier for builders to innovate and create great software? If so, Amazon Software Builder Experience (ASBX) may be the place for you. Created in 2022, ASBX has the mission of creating the world’s best builder experience across tens of thousands of software engineers across both Amazon and AWS.
Builder Insights works at the core of ASBX, shaping what it means to create the world’s best software builder experience. How do we reduce friction and toil for builders, enabling them to have more time to build features and capabilities that will delight Amazon’s customer? Where should we invest in tooling, automation, knowledge discovery, training, etc. to create the biggest benefits for builders? How do we inform managers what “good” looks like compared to teams similar to them? These are just a few of the challenges we are tackling right now.

We are looking for a passionate and hardworking scientist to use data to discover insights and turn those insights into actionable recommendations and products that improve the experience of builders across Amazon. As a data scientist on the Builder Insights team, you will help conduct rigorous science for the organization, with a focus on discovery, research, and application of generated insights into science-enabled products and features. You will have exposure to senior leadership as we communicate results and provide scientific guidance to the business. This role will also collaborate with scientists across organizations to influence science roadmaps and disseminate research.

You will work with engineers to onboard data, perform scientifically rigorous insight discovery and research, and develop the right statistical and machine learning model-based solutions to deliver impact for builders. You will solve ambiguous problems, working with stakeholders to determine the right questions to ask and developing the roadmap for delivering results. You will apply analytical abilities, business understanding, and technical expertise to identify specific and actionable opportunities to solve existing business problems and look around corners for future opportunities. You will synthesize and communicate insights and recommendations to audiences of varying levels of technical sophistication to influence investment into builder experience improvements through data-backed solutions.



Key job responsibilities
• Lead projects, requiring both business and technical domain knowledge, and drive solutions to complex or ambiguous problems with limited guidance.
• Create models and analyses that affect important business decisions.
• Review analyses of other scientists and provide feedback.
• Employ scientifically rigorous standards across multiple data science disciplines, knowing what trade-offs to make to deliver results.
• Build models using Python, R, etc. (and ability to access data using Spark, SQL, or similar)
• Proficiently use at least one common data science language to develop models (Python, R, etc.) and process data (Spark, SQL, etc.).
• Communicate verbally and in writing to business customers with various levels of technical knowledge, educating them about our systems, as well as sharing insights and recommendations



About the team
The data science team in Builder Insights believes Are Right, A Lot means listening to diverse points of view and building a culture of inclusivity where every team member can contribute. It's only when we work together and include everyone that the best ideas can shine through, and that's when we have the most impact for our customers. You can let your Ownership shine on this team! - we wear different hats, getting involved with product strategy, building infrastructure, and everything in between. We have an innate desire to Learn & Be Curious and Dive Deep as engineers and scientists.

AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services.


Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Hybrid Work
We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.