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Evening Amazon Data Science Jobs (NOW HIRING)

The Marketing Data Science team within Salesforce's Chief Data Office is seeking an experienced ... Amazon data lakes, multiple Salesforce orgs, Informatica MDM, and graph databases. A key success ...

The Marketing Data Science team within Salesforce's Chief Data Office is seeking an experienced ... Amazon data lakes, multiple Salesforce orgs, Informatica MDM, and graph databases. A key success ...

The Marketing Data Science team within Salesforce's Chief Data Office is seeking an experienced ... Amazon data lakes, multiple Salesforce orgs, Informatica MDM, and graph databases. A key success ...

Data Scientist III - AMZ9971313

Seattle, WA · On-site

$165.01K - $215.30K/yr

Own the data science elements of various products to help with data-based decision making, product ... Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments ...

Data Scientist III - AMZ9442729

Seattle, WA · On-site

$163.32K - $215.30K/yr

AMAZON.COM SERVICES LLC Offered Position: Data Scientist III Job Location: Seattle, Washington Job Number: AMZ9442729 Position Responsibilities: Own the data science elements of various products to ...

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Evening Amazon Data Science information

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$44.5K

$129.7K

$177.5K

How much do evening amazon data science jobs pay per year?

As of May 29, 2026, the average yearly pay for evening amazon data science in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Evening Amazon Data Science professional, and why are they important?

To thrive as an Evening Amazon Data Science professional, you need a strong background in statistics, machine learning, and data analysis, typically supported by a relevant degree in computer science, mathematics, or a related field. Proficiency with tools like Python, SQL, AWS services (such as Redshift or S3), and data visualization platforms is essential, along with experience using version control systems. Strong communication skills, problem-solving abilities, and adaptability to work independently during non-standard hours help you stand out in this role. These skills ensure you can effectively derive insights, collaborate across teams asynchronously, and support data-driven decision-making in Amazon’s dynamic environment.

What are some common challenges faced by data scientists working evening shifts at Amazon, and how can they be managed?

Data scientists working evening shifts at Amazon may face challenges such as coordinating with colleagues in different time zones, maintaining effective communication with daytime teams, and managing work-life balance. To overcome these hurdles, it's helpful to leverage collaborative tools like Slack or Amazon Chime for asynchronous communication, schedule overlap meetings when possible, and establish clear expectations with team members. Additionally, evening shift roles can offer the advantage of uninterrupted focus time for deep analysis and model development, which can contribute to higher productivity and skill growth.

What is an Evening Amazon Data Science job?

An Evening Amazon Data Science job typically involves working as a data scientist at Amazon during evening hours, either as part of a flexible schedule or to cover specific business needs. Data scientists at Amazon analyze large datasets, develop predictive models, and provide insights to improve products, services, or operations. Working evening shifts may be ideal for those seeking non-traditional hours or balancing other commitments. Responsibilities are similar to daytime roles but may require additional collaboration with global teams or support for time-sensitive projects.

What is the difference between Evening Amazon Data Science vs Amazon Data Analyst?

AspectEvening Amazon Data ScienceAmazon Data Analyst
Required CredentialsBachelor's or Master's in Data Science, Statistics, or related fields; programming skills in Python/RBachelor's degree in Data Analysis, Business, or related fields; proficiency in Excel, SQL
Work EnvironmentFocus on developing models, algorithms, and advanced analytics during evening shiftsData reporting, visualization, and supporting business decisions, often during regular hours
Employer & Industry UsageUsed in tech and e-commerce sectors for machine learning and predictive modelingCommon in retail, e-commerce, and logistics for data reporting and insights

While both roles involve working with data at Amazon, Evening Amazon Data Science focuses on advanced analytics and model development during evening hours, whereas Amazon Data Analysts primarily handle data reporting and insights during regular hours. The roles differ in technical complexity and daily responsibilities but share a common goal of leveraging data to improve business outcomes.

More about Evening Amazon Data Science jobs
What cities are hiring for Evening Amazon Data Science jobs? Cities with the most Evening Amazon Data Science job openings:
What are the most commonly searched types of Amazon Data Science jobs? The most popular types of Amazon Data Science jobs are:
What states have the most Evening Amazon Data Science jobs? States with the most job openings for Evening Amazon Data Science jobs include:
Manager, Data Science, Outbound Communications

Manager, Data Science, Outbound Communications

Amazon

Seattle, WA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 23 days ago


Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 6,784 frontline employees who took The Breakroom Quiz

7th of 39 rated national retailers


Job description

Are you passionate about using data science and machine learning to optimize how hundreds of millions of customers experience communications from the world's most customer-centric company? Join the Outbound Communications Intelligence team at Amazon, where you will lead the development of scalable/robust advanced AI based methods like LLMs and RL to personalize the relevance, frequency and timing of messages across push, email, WhatsApp, and SMS channels reaching 250M+ global customers every week. You will lead the insights arm to build highly accurate and world-class self-service analytics solutions that guide the short- and long-term investments for the business.
Key job responsibilities
You will lead applied scientists, data scientists and business intelligence engineers to:
- Optimize Outbound's inbox management and planning system to personalize frequency, send-time and relevance bar of our messages to customers.
- Design and execute large-scale experiments such as multi-arm elasticity tests or RCTs to measure and improve incrementality/performance of our models.
- Drive development of HVA propensity models (opt-out, purchase, etc.) to drive intended behavior of customers to their next stage of shopping and engagement with Amazon.
- Drive AI-based transformation in data accuracy and reporting: migrating and enhancing the self-serve analytics capabilities developed by the team, automating WBR preparation, building anomaly detection, etc.
- Own financial planning frameworks for outbound performance including QxG/HVE forecasting and ROI measurement for paid channel investments.
In addition, you will:
- Hire, develop, and mentor scientists and BIEs while partnering cross-functionally with engineering, product, marketing, and partner science teams (CBA, P13N, CFV) to productionize solutions at scale.
- Create, align and evolve your team's roadmap by prioritizing across multiple competing priorities using high judgement decisions.
BASIC QUALIFICATIONS
- 5+ years of building quantitative solutions as a scientist or science manager experience
- 2+ years of scientists or machine learning engineers management experience
- 5+ years of applying statistical models for large-scale application and building automated analytical systems experience
- Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field
- Knowledge of Python or R or other scripting language
PREFERRED QUALIFICATIONS
- Experience in a least one area of Machine Learning (NLP, Regression, Classification, Clustering, or Anomaly Detection)
- Experience with fairness in machine learning and artificial intelligence to detect and remove bias in ML/AI systems
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.
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 https://amazon.jobs/en/benefits.
USA, WA, Seattle - 175,100.00 - 236,900.00 USD annually

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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