About this opportunity
Amazon lists this Senior Applied Scientist, Ad Measurements Science (Advertising) opportunity in new york, New York. Review the employer’s description below for duties, qualifications and application requirements.
Job description
Senior Applied Scientist, Ad Measurements Science
Job ID: | Amazon.com Services LLC
The Ads Measurement Science team in the Measurement, Ad Tech, and Data Science (MADS) team of Amazon Ads serves a centralized role developing solutions for a multitude of performance measurement products. We create solutions which measure the comprehensive impact of advertiser's ad spend, including sales impacts both online and offline and across timescales, and provide actionable insights that enable our advertisers to optimize their media portfolios. We also own the science solutions for AI tools that unlock new insights and automate high‑effort customer workflows, such as custom query and report generation based on natural language user requests. We leverage a host of scientific technologies to accomplish this mission, including Generative AI, classical ML, causal inference, natural language processing, and computer vision.
As a Senior Applied Scientist on the team, you will be at the forefront of innovation, developing measurement solutions end‑to‑end from inception to production. You will set the technical vision and innovate on behalf of our customers. You will propose, design, analyze, and productionize models to provide novel measurement insights to our customers. You will partner with engineering to deploy these solutions into production. You will work with key stakeholders from various business teams to enable advertisers to act upon those metrics.
Key job responsibilities
Lead the development of ad measurement models and solutions that address the full spectrum of an advertiser's investment, focusing on scalable and efficient methodologies.
Collaborate closely with cross‑functional teams including engineering, product management, and business teams to define and implement measurement solutions.
Use state‑of‑the‑art scientific technologies including Generative AI, Classical Machine Learning, causal inference, natural language processing, and computer vision to develop state‑of‑the‑art models that measure the impact of ad spend across multiple platforms and timescales.
Drive experimentation and the continuous improvement of ML models through iterative development, testing, and optimization.
Translate complex scientific challenges into clear and impactful solutions for business stakeholders.
Mentor and guide junior scientists, fostering a collaborative and high‑performing team culture.
Foster collaborations between scientists to move faster, with broader impact.
Regularly engage with the broader scientific community with presentations, publications, and patents.
A day in the life
You will solve real‑world problems by getting and analyzing large amounts of data, generating business insights and opportunities, designing simulations and experiments, and developing statistical and ML models. The team is driven by business needs, which requires collaboration with other scientists, engineers, and product managers across the advertising organization. You will prepare written and verbal presentations to share insights to audiences of varying levels of technical sophistication.
About the team
We are a team of scientists across applied, research, data science, and economics disciplines. You will work with colleagues with deep expertise in ML, NLP, CV, Gen AI, and causal inference with a diverse range of backgrounds. We partner closely with top‑notch engineers, product managers, sales leaders, and other scientists with expertise in the ads industry and on building scalable modeling and software solutions.
Basic Qualifications
3+ years of building machine learning models for business application experience
PhD, or Master’s degree and 6+ years of applied research experience
Knowledge of programming languages such as C/C++, Python, Java, or Perl
Experience programming in Java, C++, Python or a related language
Experience with neural deep learning methods and machine learning
Preferred Qualifications
Experience with modeling tools such as R, scikit‑learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy, etc.
Experience with large‑scale distributed systems such as Hadoop, Spark, etc.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
The base salary range for this position is listed below. Your Amazon package will include sign‑on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at
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Worksite address
new york, NY, 10261, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.