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Job Details
Posted date: Oct 02, 2024
There have been 185 jobs posted with the title of Applied Scientist all time at Amazon.There have been 185 Applied Scientist jobs posted in the last month.
Location: Austin, TX
Estimated salary: $179,100
Range: $136,000 - $222,200
Description
Amazon Web Services (AWS) is building a world-class marketing organization, and we are looking for an experienced Applied Scientist to join the central data and science organization for AWS Marketing. You will lead AWS Measurement, targeting, recommendation, forecasting related AI/ML products and initiatives, and own mechanisms to raise the science and measurement standard. You will work with economists, scientists and engineers within the team, and partner with product and business teams across AWS Marketing to build the next generation marketing measurement, valuation and machine learning capabilities directly leading to improvements in our key performance metrics.A successful candidate has an entrepreneurial spirit and wants to make a big impact on AWS growth. You will develop strong working relationships and thrive in a collaborative team environment. You will work closely with business leaders, scientists, and engineers to translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of highly scalable distributed services. The ideal candidate will have experience with machine learning models and causal inference. Additionally, we are seeking candidates with strong rigor in applied sciences and engineering, creativity, curiosity, and great judgment.
You will work on high-impact, high-visibility products, with your work improving the experience of AWS leads and customers.
Key job responsibilities
- Lead the design, development, deployment, and innovation of advanced science models in the strategic area of marketing measurement and optimization.
- Partner with scientists, economists, engineers, and product leaders to break down complex business problems into science approaches.
- Understand and mine the large amount of data, prototype and implement new learning algorithms and prediction techniques to improve long-term causal estimation approaches.
- Design, build, and deploy effective and innovative ML solutions to improve components of our ML and causal inference pipelines.
- Publish and present your work at internal and external scientific venues in the fields of ML and causal inference.
- Influence long-term science initiatives and mentor other scientists across AWS.
Qualifications
- 3+ years of building models for business application experience- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
Extended Qualifications
- Experience in professional software development- Advanced proficiency with statistical modeling, experimental design, and machine learning algorithms
- Patents or publications at top-tier peer-reviewed conferences or journals
- Experience in Advertising, Measurement or Causal Inference
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 $136,000/year in our lowest geographic market up to $222,200/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.
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