Job Description
We are hiring a Data Scientist who is excited about delivering cutting-edge causal inference models for Amazon Web Services (AWS). Our value comes from understanding how business inputs translate into revenue for the company. Specifically, we measure the effectiveness of sales head count, customer incentive programs, and other revenue drivers to determine their incremental benefit to AWS.
Key job responsibilities
This role builds and continuously improves machine learning models that provide recommendations for improving AWS business performance. The role will work with executives, program owners, Finance, and technical peers to execute on multi-year research projects that drive step change growth for the business. This role will help develop and implement science best practices for the team in partnership with other scientists, economists, and engineers. The role will also be an important collaborator with other technical and business teams at AWS, especially those working on productivity and sales resource allocation.
A day in the life
Our team takes big swings and works on really hard, cross-organizational problems. We ask people to grow their skills and stretch, and we do it in a supportive and fun environment. It’s about empirically measured impact, advancement, and fun.
About the team
Our group is technically rigorous. Our leaders are here for you and to enable you to be successful. We are communication centric since being able to explain what we do ensures high success rates and lowers administrative churn. And if it’s not fun, what’s the point?- 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
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.
Key job responsibilities
This role builds and continuously improves machine learning models that provide recommendations for improving AWS business performance. The role will work with executives, program owners, Finance, and technical peers to execute on multi-year research projects that drive step change growth for the business. This role will help develop and implement science best practices for the team in partnership with other scientists, economists, and engineers. The role will also be an important collaborator with other technical and business teams at AWS, especially those working on productivity and sales resource allocation.
A day in the life
Our team takes big swings and works on really hard, cross-organizational problems. We ask people to grow their skills and stretch, and we do it in a supportive and fun environment. It’s about empirically measured impact, advancement, and fun.
About the team
Our group is technically rigorous. Our leaders are here for you and to enable you to be successful. We are communication centric since being able to explain what we do ensures high success rates and lowers administrative churn. And if it’s not fun, what’s the point?- 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
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.
