ZipRecruiter

Log In

1

Evening Amazon Data Science Jobs (NOW HIRING)

Amazon

Data Scientist II, NASC S&OP

Bellevue, WA

The Sort Center network is the critical Middle-Mile solution in the Amazon Transportation Services ... Key job responsibilities - Development of scalable data science solutions catering to volume and ...

Amazon

Data Scientist II, NASC S&OP

Bellevue, WA · On-site

The Sort Center network is the critical Middle-Mile solution in the Amazon Transportation Services ... Key job responsibilities - Development of scalable data science solutions catering to volume and ...

Amazon

Data Scientist, Prime Video

Seattle, WA · On-site

... Amazon MGM Studios-produced series and movies; licensed fan favorites; and exclusive access to ... You'll be part of an embedded science team on projects that are fast-paced, challenging, and ...

Amazon

Data Scientist III - AMZ9803634

San Diego, CA · On-site

$159K - $215K/yr

AMAZON.COM SERVICES LLC Offered Position: Data Scientist III Job Location: San Diego, California Job Number: AMZ9803634 Position Responsibilities: Own the data science elements of various products to ...

Amazon

Data Engineer II, OTS - Data ANCHOR Team

Austin, TX

$113K - $136K/yr

As a Data Engineer, you will build and maintain scalable data pipelines and AI/ML-ready data infrastructure that power AI-driven operational insights and Data Science initiatives across Amazon ...

Amazon

Data Engineer II, OTS - Data ANCHOR Team

Austin, TX

$113K - $136K/yr

As a Data Engineer, you will build and maintain scalable data pipelines and AI/ML-ready data infrastructure that power AI-driven operational insights and Data Science initiatives across Amazon ...

Tatari

Data Science Manager

Los Angeles, CA

$160K - $220K/yr

... Amazon, Google, Meta, Microsoft, and Yahoo, Tatari continues to scale rapidly as TV advertising ... We're looking for a Data Science Manager to lead our growing AI product data science function. This ...

Tatari

Data Science Manager

San Francisco, CA

$160K - $220K/yr

... Amazon, Google, Meta, Microsoft, and Yahoo, Tatari continues to scale rapidly as TV advertising ... We're looking for a Data Science Manager to lead our growing AI product data science function. This ...

Tatari

Data Science Manager

Los Angeles, CA · On-site

$160K - $220K/yr

... Amazon, Google, Meta, Microsoft, and Yahoo, Tatari continues to scale rapidly as TV advertising ... We're looking for a Data Science Manager to lead our growing AI product data science function. This ...

Ztek Consulting INC

Data Scientist

Charlotte, NC · On-site

Design and implement end-to-end machine learning ML pipelines using services such as Amazon ... Work with stakeholders to translate business objectives into data science solutions and actionable ...

next page

Showing results 1-20

All JobsEvening Amazon Data Science Jobs

Evening Amazon Data Science information

See salary details

$44.5K

$129.7K

$177.5K

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

As of Jul 11, 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 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 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.

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 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.
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:
What job categories do people searching Evening Amazon Data Science jobs look for? The top searched job categories for Evening Amazon Data Science jobs are:
Evening Amazon Data Science jobs near you
Infographic showing various Evening Amazon Data Science job openings in the United States as of July 2026, with employment types broken down into 1% Locum Tenens, 90% Full Time, 7% Part Time, and 2% Contract. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.
Director, Data Science

Director, Data Science

Fidelity Investments

Durham, NC • On-site

Full-time

Retirement

Re-posted yesterday

Fidelity Investments rating

8.7

Company rating: 8.7 out of 10

Based on 266 frontline employees who took The Breakroom Quiz

17th of 148 rated financial services

Job description


Position Description:
Leads and oversees end-to-end data science initiatives, guiding teams through data cleansing, preparation, annotation, feature engineering, exploratory analysis, and model development. Provides strategic direction on Machine Learning (ML) pipeline architecture, ensures alignment with business objectives, and drives cross-functional collaboration to deliver scalable, high-impact solutions. Draws on in-depth knowledge of the business or function to provide business unit-wide solutions by building, testing and monitoring AI models. Researches and recommends new technologies, and seizes opportunities by staying abreast of publications, tools, and techniques from the global Artificial Intelligence (AI/ML) community, in support of the strategic direction of the business unit and to achieve business-unit-wide solutions.
Primary Responsibilities:
  • Identifies business opportunities and evaluates best approaches for predictive or prescriptive analytics.
  • Implements best practices for model development, iteration, as well as code management and conducts code reviews.
  • Draws key business insights from advanced quantitative analyses and presents findings to broader audience.
  • Leads the design and deployment of advanced analytics solutions that convert raw data into actionable intelligence.
  • Delivers scalable insights, while aligning analytics infrastructure with business priorities.
  • Directs the development and integration of analytics frameworks that transform raw data into strategic insights.
  • Ensures solutions are scalable, business-aligned, and drive data-informed decision-making across the organization.
  • Leads and oversees the full AI/ML lifecycle -- data ingestion, model development, training, deployment, and monitoring.
  • Identifies and consults with internal and external technical resources to produce cross-company strategic designs.
  • Consults on deployment of major project deliverables.
  • Initiates and drives project or strategy discussions with users or external groups to resolve issues.
  • Sets vision, goals, and direction of team/organization.
  • Plans and leads organization-wide initiatives.
  • Provides leadership, technical supervision, and expertise to multiple teams in broad technical areas on complex organization-wide projects.
  • Advises senior management on technical strategy.
  • Regularly provides guidance, training, and coaching to other team members for performance and career development.
  • Identifies and plans for future resource needs.

Education and Experience:
Bachelor's degree in Analytics, Computer Science, Data Science, Operations Research, Economics, or a closely related field (or foreign education equivalent) and six (6) years of experience as a Director, Data Science (or closely related occupation) designing and building complex and scalable Artificial Intelligence (AI) pipelines to improve customer experience and drive business results in the financial services industry.
Or, alternatively, Master's degree in Analytics, Computer Science, Data Science, Operations Research, Economics, or a closely related field (or foreign education equivalent) and four (4) years of experience as a Director, Data Science (or closely related occupation) designing and building complex and scalable Artificial Intelligence (AI) pipelines to improve customer experience and drive business results in the financial services industry.
Skills and Knowledge:
Candidate must also possess:
  • Demonstrated Expertise ("DE") developing supervised and unsupervised Machine Learning (ML) algorithms -- regression, gradient boosting trees/random forest, neural network, feature selection/reduction, clustering, and parameter tuning -- using R, Python, and SAS programming languages; and analyzing and evaluating model results by creating data visualizations and business intelligence reports in Tableau and Adobe Analytics.

  • DE performing data wrangling and feature engineering for large, complex data across Cloud and on-premise data warehouses -- Oracle, Greenplum/Postgres, Hadoop/Hive, Snowflake, S3, and Redis -- using SQL, Python, and database specific SQL; standardizing and optimizing complex queries using database techniques -- partitioning and parallel processing; aggregating time series and transaction tables; creating appropriate features for modeling out of structured and unstructured data; detecting and preventing data leakage and model biases through model fairness measures using open-source AI fairness and ethics libraries.

  • DE analyzing technology solutions for supporting model deployment and integration in Cloud and on premise environments; and building model deployment and integration workflows on Amazon Web Services (AWS), on-premise Hadoop, and UNIX platforms through Git, Jenkins, Python scripts, cron jobs, step functions, Docker images, and APIs.

  • DE migrating existing AI/ML processes from on-premise environments to AWS platforms, using Extract- Transform-Load (ETL) procedures, Python, and Docker containers; creating data quality guardrails to validate model inputs and outputs using ICEDQ; and addressing financial services Cloud security constraints and record systems for workplace services -- 401(K), defined benefits, and workplace compensation and retirement plans, using AWS security tools.

#PE1M2
#LI-DNI
Certifications:
Category:
Data Analytics and Insights
Please be advised that Fidelity's business is governed by the provisions of the Securities Exchange Act of 1934, the Investment Advisers Act of 1940, the Investment Company Act of 1940, ERISA, numerous state laws governing securities, investment and retirement-related financial activities and the rules and regulations of numerous self-regulatory organizations, including FINRA, among others. Those laws and regulations may restrict Fidelity from hiring and/or associating with individuals with certain Criminal Histories.

What Fidelity Investments employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply