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Data Science Machine Learning Jobs (NOW HIRING)

Principal Data Scientist

Oakland, CA ยท On-site

$128 - $148/hr

Master's Degree in Data Science, Machine Learning, Computer Science, Civil Engineering, Mechanical Engineering, Electrical Engineering, Statistics, or equivalent field. * Experience in Data Science ...

Data Science / Machine Learning Project-level containerized stacks managed through Nexus Coco+ and VSCode as primary IDE/tooling environments Snowflake Azure ChatGPT A proprietary DataScience CLI ...

The Data Science Analyst is responsible for using data science, machine learning, statistical modeling, and advanced analytics to solve complex business problems across Supply Chain and Operations.

The Data Science Analyst is responsible for using data science, machine learning, statistical modeling, and advanced analytics to solve complex business problems across Supply Chain and Operations.

Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, or related quantitative field; 3+ years of experience in Data Science, Machine Learning ...

Expertise in machine learning statistical modelling and data thoughtfulness to develop and implement advanced algorithms and thoughtful solutions * Manage end-to-end data science projects ensuring ...

Master's degree or PhD in Data Science, Statistics, Computer Science, Machine Learning, or related field, or equivalent experience. * 3+ years of experience in data science, machine learning ...

Effectively communicates the data science / machine learning approach and how it will meet and address objectives to business partners. * Advocates and educates business partners on the machine ...

Showing results 21-40

Data Science Machine Learning information

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$37.5K

$122.7K

$196.5K

How much do data science machine learning jobs pay per year?

As of Sep 2, 2026, the average yearly pay for data science machine learning in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is data science machine learning?

Data science machine learning refers to the use of algorithms and statistical models to analyze and draw insights from complex data sets. In this field, professionals use machine learning techniques to build predictive models, automate decision-making processes, and uncover patterns in data. Machine learning is a core component of data science, enabling systems to improve their performance over time without being explicitly programmed. Data scientists with machine learning expertise are in high demand across industries like healthcare, finance, and technology.

What are the key skills and qualifications needed to thrive as a data science machine learning professional?

To thrive as a Data Science Machine Learning professional, you need a strong background in statistics, programming (usually Python or R), and a solid understanding of machine learning algorithms, often supported by a degree in computer science, mathematics, or a related field. Familiarity with tools like TensorFlow, scikit-learn, SQL databases, and cloud platforms, as well as certifications such as AWS Certified Machine Learning, are typically valuable. Critical thinking, problem-solving, and effective communication are vital soft skills for interpreting data and collaborating with stakeholders. These skills enable professionals to develop robust models, extract actionable insights, and drive data-driven decision-making in organizations.

What are some common challenges faced when deploying machine learning models as a data science machine learning professional?

A frequent challenge in this role is bridging the gap between building accurate models in a controlled environment and deploying them effectively in production systems. Issues such as data drift, model performance degradation, and integration with existing IT infrastructure often arise. Collaboration with engineering and IT teams is crucial to ensure models are scalable, maintainable, and secure. Regular monitoring and updating of deployed models are also essential responsibilities to sustain their value to the business.

What is the difference between Data Science Machine Learning vs Data Analyst?

AspectData Science Machine LearningData Analyst
Required SkillsProgramming (Python, R), statistics, machine learning algorithmsData visualization, SQL, basic statistics
Work EnvironmentDeveloping models, coding, experimenting with algorithmsData reporting, dashboard creation, data cleaning
Industry UsageTech, finance, healthcare, where predictive models are neededBusiness intelligence, marketing, operations

Data Science Machine Learning professionals focus on building predictive models and algorithms using programming and advanced statistics, often working on complex projects. Data Analysts primarily interpret data through visualization and reporting to support business decisions. While both roles require data skills, Data Science Machine Learning involves more technical programming and modeling, whereas Data Analysts focus on data interpretation and presentation.

Is data science machine learning a high paying job?

Data science and machine learning roles are generally high-paying within the tech industry due to the specialized skills required, such as programming, statistical analysis, and experience with tools like Python or TensorFlow. Salaries vary based on experience, location, and company size but tend to be above average compared to many other professions.
More about Data Science Machine Learning jobs

What cities are hiring for Data Science Machine Learning jobs?

Cities with the most Data Science Machine Learning job openings:

What states have the most Data Science Machine Learning jobs?

States with the most job openings for Data Science Machine Learning jobs include:

Infographic showing various Data Science Machine Learning 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 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Data Scientist / Machine Learning Engineer

Trabus Technologies

San Diego, CA โ€ข On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 21 days ago


Job description

Data Scientist / Machine Learning Engineer
About TRABUS Technologies
TRABUS Technologies (TRABUS) is a minority-owned, Service-Disabled Veteran-Owned Small Business (SDVOSB) headquartered in San Diego, California. Since 2010, TRABUS has provided advanced wireless technology solutions, cybersecurity expertise, artificial intelligence capabilities, and engineering support to federal and commercial clients.
Recognized on the Inc. 5000 list for seven consecutive years, TRABUS is a dynamic, forward-leaning organization committed to solving complex, real-world challenges and delivering mission-ready solutions that meet and exceed customer expectations.
Position Overview
TRABUS Technologies is seeking a highly motivated Data Scientist / Machine Learning Engineer to join our growing Artificial Intelligence and Data Science team.
In this role, you will combine machine learning, data science, and software engineering skills to support a variety of AI-based projects, including resource planning for ship maintenance, marine transportation, and climate and environmental informatics.
The successful candidate will develop machine learning models that provide predictive insights and analytics for robust, web-based, full-stack AI applications supporting both government customers - including the Department of Defense (DoD), Department of Transportation (DoT), and National Oceanic and Atmospheric Administration (NOAA) - and commercial customers.
Key Responsibilities
  • Develop code to extract, clean, transform, and preprocess training datasets from disparate data formats, sources, and APIs.
  • Research, evaluate, select, and develop appropriate Machine Learning (ML) and Deep Learning (DL) algorithms and models.
  • Apply AI/ML techniques across diverse data domains, including Navy, transportation, environmental sciences, healthcare, and public safety.
  • Collaborate with the TRABUS Data Science team to develop scalable AI solutions incorporating technologies such as:
    • Large Language Models (LLMs)
    • Retrieval-Augmented Generation (RAG)
    • Prompt Engineering
    • Computer Vision
    • Natural Language Processing (NLP)
  • Work alongside AI/ML and DevOps engineers to develop automated AI workflows that continuously generate predictions and inferences.
  • Develop validation and testing routines to measure model performance and evaluate the quality and accuracy of predictions.
  • Analyze large datasets and data streams to identify patterns, trends, and actionable insights.
  • Support the integration of machine learning models into web-based and full-stack AI applications.
  • Collaborate with technical teams throughout the development, testing, integration, and deployment lifecycle.

Required Qualifications
  • Minimum of 2 years of programming experience using Python.
  • Completed coursework in Machine Learning, Deep Learning, Algorithm Design, and Data Science.
  • Knowledge and experience with Python data science and machine learning libraries such as:
    • Pandas
    • scikit-learn
    • Keras
    • TensorFlow
    • PyTorch
  • Strong Python programming skills with the ability to process and analyze large datasets and data streams.
  • Understanding of databases, data structures, and API-based ETL operations.
  • Strong working knowledge of Linux or Unix-based operating systems.
  • Familiarity with Python web frameworks such as FastAPI, Django, and Flask.
  • Experience working with Git repositories and version control.
  • Ability to work collaboratively within multidisciplinary technical teams.
  • U.S. Citizenship is required.
  • Must be able to obtain and maintain a final DoD-adjudicated Secret security clearance.

Desired Qualifications
  • Current DoD-adjudicated Secret security clearance.
  • Strong knowledge of DevOps tools, processes, and best practices.
  • Experience working with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.
  • Familiarity with Agile software development methodologies.
  • Experience working within Agile development environments.
  • Experience with Continuous Integration/Continuous Deployment (CI/CD) pipelines.
  • Proficiency with Microsoft Office applications.
  • Strong written and verbal communication skills.
  • Strong attention to detail and commitment to procedural compliance.
  • Ability to manage multiple responsibilities and priorities while meeting established deadlines.

Education
  • Bachelor's degree in Computer Science, Computer Engineering, Data Science, or another related STEM discipline.
  • Master's degree preferred.

Benefits
TRABUS Technologies offers a competitive compensation package and comprehensive employee benefits, including:
  • Paid Time Off (PTO)
  • Paid Holidays
  • Health Insurance
  • Dental Insurance
  • Vision Insurance
  • Flexible Spending Account (FSA)
  • 401(k)
  • Life and AD&D Insurance

Equal Employment Opportunity
TRABUS Technologies is an Equal Employment Opportunity Employer. We are committed to the principles of equal employment opportunity and will not discriminate against any employee or applicant for employment because of race, color, religion, sex, national origin, age, disability, veteran status, or any other status protected by applicable federal, state, or local discrimination laws.