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Amazon Data Science Jobs in Florida (NOW HIRING)

Deloitte

Databricks Data Engineer

Miami, FL · On-site

$109K - $131K/yr

Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP) * Ability to travel 50 ... Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, Mathematics ...

Deloitte

Databricks Data Engineer

Tampa, FL · On-site

$108K - $129K/yr

Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP) * Ability to travel 50 ... Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, Mathematics ...

JP Morgan Chase

Applied AI/ML Lead

Tampa, FL · On-site

Leverage Amazon Bedrock to explore foundation model capabilities for intelligent document ... Computer Science, Mathematics, Operations Research, Data Science. * 7+ years of experience in ...

JPMorgan Chase & Co.

Applied AI/ML Lead

Tampa, FL · On-site

Leverage Amazon Bedrock to explore foundation model capabilities for intelligent document ... Computer Science, Mathematics, Operations Research, Data Science. * 7+ years of experience in ...

JPMorgan Chase & Co

Applied AI/ML Lead

Tampa, FL

Leverage Amazon Bedrock to explore foundation model capabilities for intelligent document ... Computer Science, Mathematics, Operations Research, Data Science. * 7+ years of experience in ...

Ascension Federal Services Inc.

Data Architect

Tallahassee, FL · On-site

$60.50 - $77.75/hr

Bachelor's degree in Computer Science, Information Technology, or related field * Proven experience ... Knowledge of business intelligence and analytics tools (e.g., Power BI, Tableau, Amazon Quick Sight)

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All JobsAmazon Data Science JobsAmazon Data Science Jobs in Florida

Amazon Data Science information

See Florida salary details

$34.4K

$123.3K

$182K

How much do amazon data science jobs pay per year?

As of Jun 16, 2026, the average yearly pay for amazon data science in Florida is $123,317.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,800.00 and $127,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Amazon Data Science position, and why are they important?

To thrive as an Amazon Data Science professional, you need strong analytical abilities, expertise in statistics and machine learning, and a solid educational background in computer science, mathematics, or a related field. Proficiency in programming languages such as Python or R, familiarity with big data tools like AWS, Spark, or Hadoop, and relevant certifications (e.g., AWS Certified Data Analytics) are often required. Effective communication, business acumen, and collaborative problem-solving set exceptional candidates apart. These skills are crucial for transforming complex data into actionable insights that drive impactful business decisions at Amazon.

What types of projects and challenges can I expect as an Amazon Data Science team member?

As an Amazon Data Science team member, you can expect to work on projects ranging from optimizing supply chains and recommendation systems to improving customer experiences and forecasting demand. Daily responsibilities often involve analyzing large data sets, building predictive models, and collaborating closely with product managers, software engineers, and business leaders. The pace is fast, with opportunities to tackle complex problems that have a direct impact on Amazon’s customers and operations. You’ll also have the chance to grow your skills through cross-team projects, participation in internal workshops, and exposure to emerging data science technologies.

What is an Amazon Data Science job?

An Amazon Data Science job involves leveraging data to drive business decisions, optimize operations, and enhance customer experiences. Data scientists at Amazon work with machine learning, statistical modeling, and big data technologies to analyze vast datasets and generate actionable insights. They collaborate with engineering, product, and business teams to develop data-driven solutions for challenges such as recommendation systems, demand forecasting, and fraud detection. Strong programming skills in Python or Scala, expertise in SQL, and experience with AWS tools are commonly required.

What are the most commonly searched types of Amazon Data Science jobs in Florida? The most popular types of Amazon Data Science jobs in Florida are:
What cities in Florida are hiring for Amazon Data Science jobs? Cities in Florida with the most Amazon Data Science job openings:
Amazon Data Science jobs near you
Infographic showing various Amazon Data Science job openings in Florida as of June 2026, with employment types broken down into 80% Full Time, 18% Part Time, and 2% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $123,317 per year, or $59.3 per hour.

Development Engineer

Power Systems Mfg., LLC

Jupiter, FL • On-site

Full-time

Posted 21 days ago

Job description

POSITION: Development Engineer, Monitoring & Diagnostics

LOCATION: Jupiter, Florida / Hybrid

STATUS: Salaried Non-Exempt


JOB SUMMARY

ESSENTIAL DUTIES AND RESPONSIBILITIES

The essential functions of the job include, but are not limited to, the following:

  • Utilize and expand AWS Cloud infrastructure to enhance data analytics and monitoring capabilities (AWS full stack development, EC2, S3, Lambda, Amplify)
  • Utilize AI models for knowledge base agent/digital twin of gas turbine.
  • Develop/maintain software for monitoring, analyzing and graphically representing gas turbine operations.
  • Continuously refine/train models to mimic real life engine behavior, minimize false alarms, and predict gas turbine alarms before they occur
  • Work with operational team to support and troubleshoot issue with customer data and cloud infrastructure
  • Continuously improve the OSIsoft PI system architecture
  • Other duties as assigned


MINIMUM REQUIREMENTS

  • Education: Bachelor’s degree in Computer Science, Data Science, Data Analytics, Mechanical Engineering, or a related quantitative/technical field.
  • Generative AI & ML: Practical experience with Machine Learning (ML) and Artificial Intelligence (AI) frameworks. Familiarity with Large Language Models (LLMs) and Foundational Models via platforms like Amazon Bedrock.
  • Full-Stack Development: Understanding of AWS Full-Stack development workflows, including API Management, IAM roles, and cloud security best practices.
  • AWS Cloud Ecosystem: Hands-on experience with AWS Cloud Architecture. Proficiency in core services including EC2 (Compute), S3 (Storage), and AWS Lambda (Serverless).
  • Programming Languages: Proficiency in at least one modern language: Python, TypeScript, C#, or MATLAB.
  • DevOps & Tools: Basic knowledge of Software Development Life Cycle (SDLC), Version Control (Git/GitHub), and Continuous Integration/Continuous Deployment (CI/CD) pipelines.
  • Methodology: Familiarity with Agile/Scrum environments and iterative development processes.
  • Data Analysis: Strong aptitude for data visualization and data modeling.
  • DataBase experience: Experience with SQL and noSQL databases.

Preferred Skills/Experience

  • AWS Certifications: Active certifications such as AWS Certified Developer, Solutions Architect, or Machine Learning – Specialty.
  • Advanced AI/ML: Exposure to Natural Language Processing (NLP), Neural Networks, or Generative AI integration via Amazon Bedrock and SageMaker.
  • Data Science Stack: Proficiency in data manipulation libraries (e.g., Pandas, NumPy, Scikit-learn)
  • Modern Web Frameworks: Experience in Full-Stack Development using React.js and TypeScript to build responsive user interfaces.
  • API Development: Knowledge of building and consuming RESTful APIs or GraphQL to connect front-end applications with cloud backends.
  • State Management: Familiarity with tools like Redux, Context API, or Zustand for complex UI logic.
  • Version Control: Mastery of Git workflows, including branching strategies, pull requests, and code reviews.
  • CI/CD Pipelines: Experience with AWS CodeCommit, GitHub Actions, or GitLab CI for automated testing and deployment.
  • Infrastructure as Code (IaC): Basic understanding of AWS CloudFormation or Terraform is a significant advantage.

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