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Entry Level Amazon Data Science Jobs (NOW HIRING)

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 ...

Amazon

Data Scientist II - AMZ27596.1

Irving, TX · On-site

$141K - $184K/yr

Amazon.com Services LLC Position: Data Scientist II - AMZ27596.1 Location: Irving, TX Multiple Positions Available: Design and implement scalable and reliable approaches to support or automate ...

Amazon

Data Scientist, Prime Video

Seattle, WA · On-site

... Amazon MGM Studios-produced series and movies; licensed fan favorites; and exclusive access to ... science team on projects that are fast-paced, challenging, and ultimately influence what millions ...

Amazon

Data Scientist, Prime Video

Seattle, WA · On-site

... Amazon MGM Studios-produced series and movies; licensed fan favorites; and exclusive access to ... science team on projects that are fast-paced, challenging, and ultimately influence what millions ...

CYNET SYSTEMS

Data Scientist

Charlotte, NC · On-site

$60 - $65/hr

Pay Range $60hr - $65hr Requirement/Must Have: * 1+ years of experience in data science or related ... Design and implement end-to-end machine learning (ML) pipelines using services such as Amazon ...

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Entry Level Amazon Data Science information

What is an entry level Amazon data science job?

An entry level Amazon data science job typically involves analyzing large datasets, building data models, and generating insights to help Amazon improve its products and services. Employees in these roles often work with teams of data scientists, engineers, and business stakeholders to solve real-world business problems. Key responsibilities may include cleaning and organizing data, using statistical and machine learning techniques, and creating visualizations to communicate findings. Entry-level positions usually require a background in statistics, computer science, or a related field, along with proficiency in programming languages like Python or R.

What are some common challenges faced by entry-level data scientists at Amazon, and how can they be addressed?

Entry-level data scientists at Amazon often encounter challenges such as working with large-scale, complex datasets and adapting to the fast-paced, results-driven environment. Navigating Amazon's proprietary tools and understanding the business context behind data projects can also be daunting at first. To overcome these challenges, new hires are encouraged to actively seek guidance from mentors, participate in team knowledge-sharing sessions, and invest time in learning Amazon's data infrastructure and workflows. Collaboration with cross-functional teams is frequent, so developing strong communication skills and a willingness to ask questions can significantly ease the transition and lead to early success.

What are the key skills and qualifications needed to thrive as an entry level Amazon data scientist, and why are they important?

To thrive as an Entry Level Data Scientist at Amazon, you typically need a strong foundation in statistics, data analysis, and programming, often supported by a degree in computer science, mathematics, or a related field. Familiarity with tools and languages such as Python, SQL, AWS, and machine learning libraries, along with experience using data visualization platforms, is highly valued. Strong problem-solving abilities, communication skills, and the ability to collaborate across teams set top candidates apart. These skills are essential to extract actionable insights from large datasets, drive data-driven decisions, and contribute effectively to Amazon’s innovative environment.

What is the difference between Entry Level Amazon Data Science vs Entry Level Amazon Data Engineering?

AspectEntry Level Amazon Data ScienceEntry Level Amazon Data Engineering
Required CredentialsBachelor's in Data Science, Statistics, or related field; Python, R skillsBachelor's in Computer Science, Software Engineering, or related; SQL, Python, Spark skills
Work EnvironmentAnalyzing data, building models, predictive analyticsBuilding data pipelines, managing data infrastructure
Employer & Industry UsageUsed across Amazon for insights, recommendations, customer behaviorSupports data infrastructure, ETL processes, data storage

Entry Level Amazon Data Science focuses on analyzing data and creating models to inform business decisions, while Entry Level Amazon Data Engineering involves building and maintaining data pipelines and infrastructure. Both roles require technical skills but differ in their core responsibilities and daily tasks.

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Entry Level Amazon Data Science jobs near you
Infographic showing various Entry Level Amazon Data Science job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Data Scientist

Ztek Consulting INC

Charlotte, NC • On-site

Contractor

Re-posted yesterday

Job description

Role Name: Data Scientist

Location: Charlotte, NC / hybrid

Type of hire: Contract

JOB DESCRIPTION:

Key Responsibilities

  • Design and implement end-to-end machine learning ML pipelines using services such as Amazon SageMaker AWS Glue AWS Lambda and Amazon S3
  • Perform data collection cleaning and feature engineering to prepare datasets for modeling
  • Develop predictive models and statistical analyses using Python R or similar tools
  • Deploy monitor and optimize ML models in production environments using AWS ML Ops best practices
  • Collaborate with data engineers to design ETL pipelines and ensure data availability and reliability
  • Utilize AWS analytics services Athena Redshift QuickSight EMR for advanced reporting and visualization
  • Work with stakeholders to translate business objectives into data science solutions and actionable insights
  • Apply AIML algorithms for use cases such as forecasting anomaly detection NLP computer vision and recommendation systems
  • Maintain compliance with security and governance standards for data management on AWSKey Responsibilities
  • Design and implement end to end machine learning ML pipelines using services such as Amazon SageMaker AWS Glue AWS Lambda and Amazon S3
  • Perform data collection cleaning and feature engineering to prepare datasets for modeling
  • Develop predictive models and statistical analyses using Python R or similar tools
  • Deploy monitor and optimize ML models in production environments using AWS ML Ops best practices
  • Collaborate with data engineers to design ETL pipelines and ensure data availability and reliability
  • Utilize AWS analytics services Athena Redshift QuickSight EMR for advanced reporting and visualization
  • Work with stakeholders to translate business objectives into data science solutions and actionable insights
  • Apply AIML algorithms for use cases such as forecasting anomaly detection NLP computer vision and recommendation systems
  • Maintain compliance with security and governance standards for data management on AWS