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Remote Amazon Optimization Jobs in Kansas (NOW HIRING)

Watch our talk at Amazon Tech Talks: StackAdapt is a remote-first company, and we are open to ... Lead the creation and optimization of advanced machine learning algorithms-from developing new ...

Watch our talk at Amazon Tech Talks: StackAdapt is a Remote First company, we are open to ... Write performance-efficient, memory-optimized code and continually refine services for reliability ...

Senior Database Administrator

Overland Park, KS · On-site +1

$46.75 - $64.50/hr

Design, recommend and implement appropriate storage to ensure optimum performance and availability ... Amazon's AWS relational database products experience preferred. Data Lake and analytics experience ...

Watch our talk at Amazon Tech Talks: StackAdapt is a Remote First company, we are open to ... optimizing web application performance across the entire stack * Experience leading large scale ...

Remote Amazon Optimization information

What is Remote Amazon Optimization?

Remote Amazon Optimization refers to the process of improving and managing product listings, advertising campaigns, and overall sales performance on Amazon from a remote location. Specialists in this role use data analysis, keyword research, and marketing strategies to enhance product visibility, increase conversions, and boost sales. They may work for brands, agencies, or as freelancers, and often collaborate with teams virtually. Typical tasks include optimizing product titles and descriptions, managing PPC ads, monitoring performance metrics, and implementing best practices for Amazon SEO.

What is the difference between Remote Amazon Optimization vs Remote Amazon PPC Specialist?

AspectRemote Amazon OptimizationRemote Amazon PPC Specialist
Primary FocusOverall product listing optimization, including keywords, images, and contentManaging and optimizing Amazon advertising campaigns
Required SkillsSEO, listing optimization, product researchAd campaign management, bid strategies, analytics
CertificationsAmazon SEO certifications, e-commerce experienceAmazon Advertising certifications, PPC expertise
Work EnvironmentRemote, e-commerce teams, product listingsRemote, marketing teams, ad platforms

Remote Amazon Optimization focuses on enhancing product listings to improve organic visibility, while Remote Amazon PPC Specialist concentrates on managing paid advertising campaigns. Both roles often overlap but serve different strategic purposes within Amazon seller operations.

What are the key skills and qualifications needed to thrive as a Remote Amazon Optimization Specialist, and why are they important?

To thrive as a Remote Amazon Optimization Specialist, you need expertise in e-commerce strategies, Amazon Seller Central, product listing optimization, and data analysis, often supported by experience in digital marketing or certifications like Amazon Advertising. Familiarity with tools such as Helium 10, Jungle Scout, and Amazon PPC platforms is typically required. Strong analytical thinking, attention to detail, and effective communication are crucial soft skills for success in this role. These skills help maximize product visibility, drive sales growth, and ensure seamless collaboration with remote teams.

What are some common challenges faced in a remote Amazon optimization role, and how can they be addressed?

One of the main challenges in a remote Amazon optimization role is staying updated with Amazon's frequently changing algorithms and policies, which can impact product visibility and sales. Additionally, effective communication with cross-functional teams, such as marketing, design, and inventory management, can be more complex when working remotely. To address these challenges, it's important to establish regular check-ins with team members, utilize project management tools, and dedicate time for continuous learning about Amazon's platform. Staying proactive and maintaining clear documentation can also help in managing optimization strategies efficiently across remote teams.
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Senior/Staff Applied Machine Learning Scientist

StackAdapt

Remote

Other

Posted 19 days ago


Job description

We are searching for a talented Senior/Staff Applied Machine Learning Scientist to join our engineering team as we continue to expand our data science efforts. Our platform is connected to thousands of publishers and advertisers worldwide and as a result, we're dealing with millions of requests each second, making billions of decisions. We utilize the latest technologies to solve challenges in traffic, data storage, machine learning, and scalability.
 
Want to learn more about our Data Science Team: https://alldus.com/ie/blog/podcasts/aiinaction-ned-dimitrov-stackadapt/
Learn more about our team culture here: https://www.stackadapt.com/careers/data-science 
Watch our talk at Amazon Tech Talks: https://www.youtube.com/watch?v=lRqu-a4gPuU
 
StackAdapt is a remote-first company, and we are open to candidates located anywhere in the US or Canada for this position.
What you'll be doing:
  • Lead the creation and optimization of advanced machine learning algorithms-from developing new methods to refining existing techniques-to enhance advertising effectiveness and ROI using deep ML expertise.
  • Own the end-to-end development of production-grade ML models: write efficient, scalable code and collaborate with Machine Learning Engineers to deploy and integrate algorithms into live systems.
  • Drive the prototyping and rigorous testing of innovative algorithms and data pipelines using historical data to validate performance and scalability; lead iterative improvements based on data-driven insights.
What you'll bring to the table:
  • 3+ years of industry experience
  • Have a Masters degree or PhD in Computer Science, Statistics, Operations Research, or a related field, with dual degrees a plus.
  • Have the ability to take an ambiguously defined task, and break it down into actionable steps
  • Have a comprehensive understanding of statistics, optimization and machine learning
  • Are proficient in coding, data structures, and algorithms
  • Enjoy working in a friendly, collaborative environment with others