Amazon
Principal Research Scientist, Measurement Science , Campaign Measurement & Optim
Amazon, Sunnyvale, California, United States, 94087
Principal Applied Scientist, Campaign Measurement & Optimization
The Campaign Measurement & Optimization (CMO) organization is looking for a Principal Research Scientist interested in solving challenging business problems in marketing measurement. Working with a team of data scientists, applied scientists, research scientists, and economists, this leader will help redefine marketing measurement at Amazon and its subsidiaries.
The CMO organization’s mission is to be the most trusted source of measurement science solutions to drive marketing investment decisions across Amazon. CMO provides incrementality and efficiency measurement services to the marketing stakeholders across Amazon’s lines of business. CMO applies deep learning based causal inference models to measure omni-channel effectiveness of marketing campaigns from these businesses worldwide. The impact and influence of the organization is tremendous, helping optimize spend decisions on a scale that exceeds many countries’ GDP. Our outputs shape Amazon product and marketing teams’ decisions and therefore how Amazon customers see, use, and value their experience with Amazon.
This is a high-impact role with opportunities to develop systems and analyze marketing effectiveness that contributes billions of dollars to the business. As a lead research scientist in the team, you will be responsible for designing and developing cutting edge measurement and optimization models, while collaborating with businesses, marketers, and software teams to solve key challenges facing the teams. Such challenges include measuring the incremental impact of multi-channel marketing portfolios, developing Deep Learning models for estimating the impact on sparse customer actions, and scaling measurement solutions for WW marketplaces. Our team members have an opportunity to be on the forefront of marketing measurement thought leadership by working on some of the most difficult problems in the industry with some of the best product managers, research scientists, economists and software developers in the business.
In this role, you will be a technical leader in Marketing science research with significant scope, impact, and high visibility. You will champion cutting edge ML models using the latest in Deep Learning, and Transformers. You will lead strategic measurement science initiatives in CMO and across various marketing teams, scaling experimentation and measurement science models, real-time inference, and cross-channel orchestration. As a successful scientist, you are an analytical problem solver who enjoys diving into data, leads development of new frameworks, is excited about investigations and algorithms, and can credibly interface between technical teams and business stakeholders. You are an expert in employing deep learning models to solve business problems, preferably in causal inference. You are a hands-on innovator who can contribute to advancing Marketing measurement technology in a B2C and B2B environment, and push the limits on what’s scientifically possible with a razor sharp focus on measurable customer and business impact. You will coach and guide junior scientists to grow the team’s talent and scale the impact of your work.
We are open to hiring candidates to work out of one of the following locations:
Irvine, CA, USA | Seattle, WA, USA | Sunnyvale, CA, USABASIC QUALIFICATIONS
Master's degree in Mathematics, Statistics, Machine Learning, or a related quantitative field7+ years of experience of designing and delivering highly efficient and effective AI/ML powered technical solutions that solve organizational business problems at scaleExpert in designing and supporting large-scale measurement and optimization systems in a production environmentExtensive experience applying theoretical models in an applied environmentDemonstrated proficiency in deep learning models, experience building production level systems for causal inferenceExpert in more than one more major programming / scripting languages (Python, Scala, PySpark or similar)Solid doc writing skillsExcellent written and verbal communication skills while addressing both technical and business people; ability to speak at a level appropriate for the audience. The ideal candidate should be able to present business cases, and document models, analyses, and results to influence important decisionsExperience coaching and reviewing work of junior ML ScientistsPREFERRED QUALIFICATIONS
PhD in Mathematics, Statistics, Machine Learning, or a related quantitative field10+ years of experience in marketing measurement science and content ranking AI/MLExperience with Generative AI, large scale distributed systemsIndependent thinker and influencer on strategic decisionsComprehension of tech stacks and could stay on top of tactical executionStrong publication record in one of the following technical topics: recommender system, optimization, reinforcement learning, time series, natural language processing, experiment system designFunctional knowledge of AWS platforms such as S3, Glue, Athena, SagemakerStrong fundamentals in problem solving, algorithm design and complexity analysisAmazon 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.
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The Campaign Measurement & Optimization (CMO) organization is looking for a Principal Research Scientist interested in solving challenging business problems in marketing measurement. Working with a team of data scientists, applied scientists, research scientists, and economists, this leader will help redefine marketing measurement at Amazon and its subsidiaries.
The CMO organization’s mission is to be the most trusted source of measurement science solutions to drive marketing investment decisions across Amazon. CMO provides incrementality and efficiency measurement services to the marketing stakeholders across Amazon’s lines of business. CMO applies deep learning based causal inference models to measure omni-channel effectiveness of marketing campaigns from these businesses worldwide. The impact and influence of the organization is tremendous, helping optimize spend decisions on a scale that exceeds many countries’ GDP. Our outputs shape Amazon product and marketing teams’ decisions and therefore how Amazon customers see, use, and value their experience with Amazon.
This is a high-impact role with opportunities to develop systems and analyze marketing effectiveness that contributes billions of dollars to the business. As a lead research scientist in the team, you will be responsible for designing and developing cutting edge measurement and optimization models, while collaborating with businesses, marketers, and software teams to solve key challenges facing the teams. Such challenges include measuring the incremental impact of multi-channel marketing portfolios, developing Deep Learning models for estimating the impact on sparse customer actions, and scaling measurement solutions for WW marketplaces. Our team members have an opportunity to be on the forefront of marketing measurement thought leadership by working on some of the most difficult problems in the industry with some of the best product managers, research scientists, economists and software developers in the business.
In this role, you will be a technical leader in Marketing science research with significant scope, impact, and high visibility. You will champion cutting edge ML models using the latest in Deep Learning, and Transformers. You will lead strategic measurement science initiatives in CMO and across various marketing teams, scaling experimentation and measurement science models, real-time inference, and cross-channel orchestration. As a successful scientist, you are an analytical problem solver who enjoys diving into data, leads development of new frameworks, is excited about investigations and algorithms, and can credibly interface between technical teams and business stakeholders. You are an expert in employing deep learning models to solve business problems, preferably in causal inference. You are a hands-on innovator who can contribute to advancing Marketing measurement technology in a B2C and B2B environment, and push the limits on what’s scientifically possible with a razor sharp focus on measurable customer and business impact. You will coach and guide junior scientists to grow the team’s talent and scale the impact of your work.
We are open to hiring candidates to work out of one of the following locations:
Irvine, CA, USA | Seattle, WA, USA | Sunnyvale, CA, USABASIC QUALIFICATIONS
Master's degree in Mathematics, Statistics, Machine Learning, or a related quantitative field7+ years of experience of designing and delivering highly efficient and effective AI/ML powered technical solutions that solve organizational business problems at scaleExpert in designing and supporting large-scale measurement and optimization systems in a production environmentExtensive experience applying theoretical models in an applied environmentDemonstrated proficiency in deep learning models, experience building production level systems for causal inferenceExpert in more than one more major programming / scripting languages (Python, Scala, PySpark or similar)Solid doc writing skillsExcellent written and verbal communication skills while addressing both technical and business people; ability to speak at a level appropriate for the audience. The ideal candidate should be able to present business cases, and document models, analyses, and results to influence important decisionsExperience coaching and reviewing work of junior ML ScientistsPREFERRED QUALIFICATIONS
PhD in Mathematics, Statistics, Machine Learning, or a related quantitative field10+ years of experience in marketing measurement science and content ranking AI/MLExperience with Generative AI, large scale distributed systemsIndependent thinker and influencer on strategic decisionsComprehension of tech stacks and could stay on top of tactical executionStrong publication record in one of the following technical topics: recommender system, optimization, reinforcement learning, time series, natural language processing, experiment system designFunctional knowledge of AWS platforms such as S3, Glue, Athena, SagemakerStrong fundamentals in problem solving, algorithm design and complexity analysisAmazon 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.
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