On a day-to-day this means building ML models, analyzing data from your recent A/B tests, and ... of search ranking by presenting proposals to Amazon's business and tech leaders. About the team We ...
On a day-to-day this means building ML models, analyzing data from your recent A/B tests, and ... of search ranking by presenting proposals to Amazon's business and tech leaders. About the team We ...
On a day-to-day this means building ML models, analyzing data from your recent A/B tests, and ... of search ranking by presenting proposals to Amazon's business and tech leaders. About the team We ...
On a day-to-day this means building ML models, analyzing data from your recent A/B tests, and ... of search ranking by presenting proposals to Amazon's business and tech leaders. About the team We ...
On a day-to-day this means building ML models, analyzing data from your recent A/B tests, and ... search ranking, and infrastructure to make it all happen at scale and efficiently.
On a day-to-day this means building ML models, analyzing data from your recent A/B tests, and ... search ranking, and infrastructure to make it all happen at scale and efficiently.
On a day-to-day this means building ML models, analyzing data from your recent A/B tests, and ... search ranking, and infrastructure to make it all happen at scale and efficiently.
On a day-to-day this means building ML models, analyzing data from your recent A/B tests, and ... search ranking, and infrastructure to make it all happen at scale and efficiently.
Own major ranking initiatives from problem definition through experimentation, launch, and ... Analyze user behavior, search logs, query-result interactions, and model performance to identify ...
Own major ranking initiatives from problem definition through experimentation, launch, and ... Analyze user behavior, search logs, query-result interactions, and model performance to identify ...
On a day-to-day this means building ML models, analyzing data from your recent A/B tests, and ... search ranking, and infrastructure to make it all happen at scale and efficiently. BASIC ...
On a day-to-day this means building ML models, analyzing data from your recent A/B tests, and ... search ranking, and infrastructure to make it all happen at scale and efficiently. BASIC ...
On a day-to-day this means building ML models, analyzing data from your recent A/B tests, and ... You will shape the future of search ranking by presenting proposals to Amazon's business and tech ...
On a day-to-day this means building ML models, analyzing data from your recent A/B tests, and ... You will shape the future of search ranking by presenting proposals to Amazon's business and tech ...
Own major ranking initiatives from problem definition through experimentation, launch, and ... Analyze user behavior, search logs, query-result interactions, and model performance to identify ...
Own major ranking initiatives from problem definition through experimentation, launch, and ... Analyze user behavior, search logs, query-result interactions, and model performance to identify ...
Own major ranking initiatives from problem definition through experimentation, launch, and ... Analyze user behavior, search logs, query-result interactions, and model performance to identify ...
Own major ranking initiatives from problem definition through experimentation, launch, and ... Analyze user behavior, search logs, query-result interactions, and model performance to identify ...
Own major ranking initiatives from problem definition through experimentation, launch, and ... Analyze user behavior, search logs, query-result interactions, and model performance to identify ...
Own major ranking initiatives from problem definition through experimentation, launch, and ... Analyze user behavior, search logs, query-result interactions, and model performance to identify ...
Own major ranking initiatives from problem definition through experimentation, launch, and ... Analyze user behavior, search logs, query-result interactions, and model performance to identify ...
Own major ranking initiatives from problem definition through experimentation, launch, and ... Analyze user behavior, search logs, query-result interactions, and model performance to identify ...
Own major ranking initiatives from problem definition through experimentation, launch, and ... Analyze user behavior, search logs, query-result interactions, and model performance to identify ...
Own major ranking initiatives from problem definition through experimentation, launch, and ... Analyze user behavior, search logs, query-result interactions, and model performance to identify ...
Own major ranking initiatives from problem definition through experimentation, launch, and ... Analyze user behavior, search logs, query-result interactions, and model performance to identify ...
Own major ranking initiatives from problem definition through experimentation, launch, and ... Analyze user behavior, search logs, query-result interactions, and model performance to identify ...
Own major ranking initiatives from problem definition through experimentation, launch, and ... Analyze user behavior, search logs, query-result interactions, and model performance to identify ...
Own major ranking initiatives from problem definition through experimentation, launch, and ... Analyze user behavior, search logs, query-result interactions, and model performance to identify ...
Own major ranking initiatives from problem definition through experimentation, launch, and ... Analyze user behavior, search logs, query-result interactions, and model performance to identify ...
Own major ranking initiatives from problem definition through experimentation, launch, and ... Analyze user behavior, search logs, query-result interactions, and model performance to identify ...
Own major ranking initiatives from problem definition through experimentation, launch, and ... Analyze user behavior, search logs, query-result interactions, and model performance to identify ...
Own major ranking initiatives from problem definition through experimentation, launch, and ... Analyze user behavior, search logs, query-result interactions, and model performance to identify ...
Own major ranking initiatives from problem definition through experimentation, launch, and ... Analyze user behavior, search logs, query-result interactions, and model performance to identify ...
Own major ranking initiatives from problem definition through experimentation, launch, and ... Analyze user behavior, search logs, query-result interactions, and model performance to identify ...
Own major ranking initiatives from problem definition through experimentation, launch, and ... Analyze user behavior, search logs, query-result interactions, and model performance to identify ...
Own major ranking initiatives from problem definition through experimentation, launch, and ... Analyze user behavior, search logs, query-result interactions, and model performance to identify ...
(USA) Staff, Product Manager - Search Ranking
Mountain View, CA · On-site
$143K - $286K/yr
You will partner closely with Engineering, Data Science, Analytics, Design, and Business teams to ... The team leads strategy and execution for complex search ranking, relevance, and product-discovery ...
(USA) Staff, Product Manager - Search Ranking
Mountain View, CA · On-site
$143K - $286K/yr
You will partner closely with Engineering, Data Science, Analytics, Design, and Business teams to ... The team leads strategy and execution for complex search ranking, relevance, and product-discovery ...
(USA) Staff, Product Manager - Search Ranking
Fremont, CA · On-site
$143K - $286K/yr
You will partner closely with Engineering, Data Science, Analytics, Design, and Business teams to ... The team leads strategy and execution for complex search ranking, relevance, and product-discovery ...
(USA) Staff, Product Manager - Search Ranking
Fremont, CA · On-site
$143K - $286K/yr
You will partner closely with Engineering, Data Science, Analytics, Design, and Business teams to ... The team leads strategy and execution for complex search ranking, relevance, and product-discovery ...
Search Ranking Analyst information
See salary details
$11K - $17K
0% of jobs
$17K - $22.9K
0% of jobs
$22.9K - $28.9K
0% of jobs
$28.9K - $34.8K
0% of jobs
$34.8K - $40.8K
0% of jobs
$40.8K - $46.7K
0% of jobs
$50.9K is the 25th percentile. Wages below this are outliers.
$46.7K - $52.7K
36% of jobs
$52.7K - $58.6K
0% of jobs
$58.6K - $64.6K
2% of jobs
The median wage is $66.6K / yr.
$64.6K - $70.5K
36% of jobs
$70.9K is the 75th percentile. Wages above this are outliers.
$70.5K - $76.5K
27% of jobs
$11K
$63.6K
$76.5K
How much do search ranking analyst jobs pay per year?
As of Aug 16, 2026, the average yearly pay for search ranking analyst in the United States is $63,611.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,000.00 and $71,500.00 per year, depending on experience, location, and employer.
What are the key skills and qualifications needed to thrive as a search ranking analyst, and why are they important?
To thrive as a Search Ranking Analyst, you need strong analytical skills, a solid understanding of SEO principles, and experience with web analytics, typically supported by a degree in marketing, computer science, or a related field. Familiarity with tools like Google Analytics, SEMrush, Ahrefs, and search engine algorithms is essential for analyzing and improving website rankings. Attention to detail, critical thinking, and effective communication are standout soft skills for interpreting data and collaborating across teams. These abilities are crucial for delivering actionable insights that drive traffic, improve visibility, and support business objectives.
What is a search ranking analyst?
Search Ranking Analysts are professionals who evaluate and optimize the relevance and quality of search engine results. They analyze how websites and web pages are ranked by search engines like Google or Bing, often using data and evaluation tools to improve search algorithms. Their work helps ensure that users receive accurate and useful results for their queries. They may be involved in tasks such as testing search results, providing feedback, and identifying trends or areas for improvement. Search Ranking Analysts typically have strong analytical skills and a good understanding of how search engines function.
What does a search ranking analyst do?
A search ranking analyst evaluates and improves the placement of websites or content in search engine results. They analyze data, monitor search performance, and use tools like SEO software to optimize rankings and increase visibility.
What are some typical challenges a search ranking analyst faces when optimizing search algorithms?
A Search Ranking Analyst often encounters challenges such as balancing relevance and diversity in search results, handling ambiguous queries, and adapting to ever-changing user behaviors. Additionally, analyzing large volumes of data to identify patterns and test algorithm changes can be complex and time-consuming. Collaborating closely with data scientists, engineers, and product managers is essential to ensure that improvements align with business goals while maintaining a positive user experience.
More about Search Ranking Analyst jobs
What job categories do people searching Search Ranking Analyst jobs look for?
The top searched job categories for Search Ranking Analyst jobs are:
Amazon rating
7.4
Based on 7,091 frontline employees who took The Breakroom Quiz
6th of 39 rated national retailers
Job description
Amazon's Search team creates ML algorithms that connect customers around the world with products that delight them. We harness machine learning at Amazon's scale to make the customer experience easier and smoother. Our impact is large.
For example, if your innovations save even 1 minute per customer per year, then for every 100 million customers, you save approximately 190 years of human effort.
Key job responsibilities
As an Applied Scientist on the Search Ranking team, you will build search ranking models that work for thousands of product types, billions of queries, and hundreds of millions of customers spread around the world. You will find the next set of big improvements to ranking, leverage large datasets to understand the complexities of customer behavior, and build ML models that work at Amazon scale. Amazon's Search ranking relies on efficient early stage ranking followed by power final stage ranking models
this role focuses on efficient models for early stage ranking phase, and techniques to personalize these models and optimize them automatically.
A day in the life
Our primary focus is improving search ranking systems. On a day-to-day this means building ML models, analyzing data from your recent A/B tests, and collaborating with partner teams on joint goals. We leverage agentic workflows to improve our scientific velocity, and partner closely with engineering teams to bring our ideas to production
You will shape the future of search ranking by presenting proposals to Amazon's business and tech leaders.
About the team
We are a team consisting of ML scientists and software engineers. Our interests span machine learning for better ranking, personalization to refine the ranking of our models, reinforcement learning to bring the benefits of exploration to search ranking, and infrastructure to make it all happen at scale and efficiently.
About Amazon
Sourced by ZipRecruiter
Amazon.com, Inc., commonly known as Amazon, is an American multinational technology company. It was founded by Jeff Bezos in 1994 and initially started as an online marketplace for books. Since then, Amazon has expanded its operations and become one of the largest e-commerce companies in the world. Amazon's primary business is its online retail platform, where customers can purchase a vast array of products, including electronics, clothing, books, home goods, and much more. The company offers a convenient and user-friendly shopping experience, with features such as fast shipping, customer reviews, and personalized recommendations. In addition to its e-commerce platform, Amazon has diversified its business into various other areas. One of its notable ventures is Amazon Web Services (AWS), a comprehensive cloud computing platform that provides services such as storage, compute power, and database management to individuals and businesses. AWS has become a leader in the cloud computing industry, powering many websites and applications worldwide. Amazon has also developed its own consumer electronics, including the popular Amazon Kindle e-reader, Fire tablets, Fire TV streaming devices, and the Alexa-powered Echo smart speakers. The Alexa voice assistant, integrated into these devices, allows users to interact with their devices using voice commands, perform tasks, and access information. Furthermore, Amazon has expanded into media and entertainment. It operates Prime Video, a streaming service that offers a wide range of movies, TV shows, and original content. Amazon Music provides a platform for streaming and purchasing digital music, while Audible offers audiobooks and other audio content. The company's commitment to customer satisfaction and convenience is demonstrated by its membership program, Amazon Prime. Prime members receive various benefits, including free two-day shipping, access to streaming services, exclusive deals, and more.
Industry
It services, book publishers, retail, real estate and computer and electronic product manufacturing
Company size
10,000+ Employees
Headquarters location
Seattle, WA, US