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Data Science Machine Learning Jobs (NOW HIRING)

Walmart

Senior Manager, Data Science

San Jose, CA · On-site

$143K - $286K/yr

As a Senior Manager, Data Science, you will lead a team of data scientists and machine learning practitioners responsible for delivering advanced analytics, AI, and machine learning solutions that ...

Beth Page tech

Data Scientist

Houston, TX · On-site

Data Science & Machine Learning: * Strong foundation in mathematics, statistics, and machine learning * Experience with exploring and extracting insights from multi-dimensional datasets * Proficiency ...

Walmart

Senior Manager, Data Science

Hayward, CA · On-site

$143K - $286K/yr

As a Senior Manager, Data Science, you will lead a team of data scientists and machine learning practitioners responsible for delivering advanced analytics, AI, and machine learning solutions that ...

Walmart

Senior Manager, Data Science

Milpitas, CA · On-site

$143K - $286K/yr

As a Senior Manager, Data Science, you will lead a team of data scientists and machine learning practitioners responsible for delivering advanced analytics, AI, and machine learning solutions that ...

Walmart

Senior Manager, Data Science

Cupertino, CA · On-site

$143K - $286K/yr

As a Senior Manager, Data Science, you will lead a team of data scientists and machine learning practitioners responsible for delivering advanced analytics, AI, and machine learning solutions that ...

Bose Corporation

Sr. Data Scientist

Framingham, MA · On-site

$120K - $165K/yr

Data science, machine learning, and analytics are a crucial part of this mission. These capabilities fuel the creation of new and innovative products, helping us to bring the right products to the ...

Walmart

Senior Manager, Data Science

Sunnyvale, CA · On-site

$143K - $286K/yr

As a Senior Manager, Data Science, you will lead a team of data scientists and machine learning practitioners responsible for delivering advanced analytics, AI, and machine learning solutions that ...

Walmart

Senior Manager, Data Science

Mountain View, CA · On-site

$143K - $286K/yr

As a Senior Manager, Data Science, you will lead a team of data scientists and machine learning practitioners responsible for delivering advanced analytics, AI, and machine learning solutions that ...

Walmart

Senior Manager, Data Science

Sunnyvale, CA · On-site

As a Senior Manager, Data Science, you will lead a team of data scientists and machine learning practitioners responsible for delivering advanced analytics, AI, and machine learning solutions that ...

Fannie Mae

Data Science Advisor

Washington, DC

You will apply expertise in data science, machine learning, AI, large-scale data processing, computational programming, and practical problem solving, while clearly explaining technical solutions to ...

Walmart

Senior Manager, Data Science

San Mateo, CA · On-site

$143K - $286K/yr

As a Senior Manager, Data Science, you will lead a team of data scientists and machine learning practitioners responsible for delivering advanced analytics, AI, and machine learning solutions that ...

Walmart

Senior Manager, Data Science

Fremont, CA · On-site

$143K - $286K/yr

As a Senior Manager, Data Science, you will lead a team of data scientists and machine learning practitioners responsible for delivering advanced analytics, AI, and machine learning solutions that ...

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All JobsData Science Machine Learning Jobs

Data Science Machine Learning information

See salary details

$37.5K

$122.7K

$196.5K

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

As of Jun 29, 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.

Which has more salary, CS or AI?

Data Science and Machine Learning roles in AI generally have higher salaries than traditional computer science positions due to specialized skills in deep learning, neural networks, and advanced algorithms. AI roles often require expertise in programming languages like Python and frameworks such as TensorFlow, which are highly valued in the job market. Salaries vary by experience, location, and industry, but AI-focused positions tend to offer higher compensation on average.

What are the key skills and qualifications needed to thrive as a Data Science Machine Learning professional, and why are they important?

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 engineers make $500,000?

Senior data science and machine learning engineers with extensive experience, advanced skills in programming, statistical analysis, and deep learning, and often working in high-demand industries or at large tech companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at executive or specialized levels.

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.

Do data scientists work with machine learning?

Data scientists often work with machine learning as a core part of their role, developing models to analyze data and make predictions. They use tools like Python, R, and libraries such as scikit-learn or TensorFlow to build and deploy machine learning algorithms. Knowledge of statistics, programming, and data manipulation is essential for this work.

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.

Which 3 jobs will survive AI?

Data science and machine learning roles are expected to persist as they require complex problem-solving, domain expertise, and creativity that AI tools currently cannot fully replicate. Jobs involving strategic decision-making, ethical considerations, and interpersonal skills, such as data analysts, AI ethics specialists, and AI system trainers, are also likely to remain in demand. Continuous learning and proficiency with AI tools will be essential for these roles to adapt and thrive.
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:
Data Science Machine Learning jobs near you
Infographic showing various Data Science Machine Learning job openings in the United States as of June 2026, with employment types broken down into 52% Full Time, 46% Part Time, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Associate Data Scientist

Carnegie Mellon University

Pittsburgh, PA • On-site

$55K - $55K/yr

Other

Posted 19 days ago

Key responsibilities

  • Work with customers to identify problems where advanced statistical techniques can be applied.

  • Plan, develop, and build prototype and final data science solutions to address cybersecurity challenges.

  • Co-author research proposals, execute studies, and present findings to sponsors and at academic conferences.

Carnegie Mellon University rating

8.6

Company rating: 8.6 out of 10

Based on 24 frontline employees who took The Breakroom Quiz

54th of 541 rated colleges and universities

Job description

What We Do:
Data Scientists at the SEI use advanced statistics, data analytics, machine learning, and artificial intelligence to help our government and industry clients research and solve cybersecurity challenges. In this role, you will work with our customers to identify areas where advanced statistical techniques can help tackle problems, plan and develop prototype solutions, and build out final products. You'll get a chance to work with elite cybersecurity professionals and university faculty to build new technologies that will influence national cybersecurity strategy for decades to come. You will co-author research proposals, execute studies, and present findings to DoW sponsors and at academic conferences.
Our team works on a wide range of projects. Our current work includes research in generative AI and large language models, computer vision, multimodal AI, agentic AI, and assurance of AI systems. Additionally, we craft metrics and experimental designs for large-scale cybersecurity research programs, develop human-in-the-loop machine learning solutions, and build classifiers to identify security vulnerabilities. If you are a data science or statistics expert with an interest in cybersecurity, we want to hear from you!
Requirements:
  • BS in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with three (3) years of experience or equivalent combination of training or experience; or MS in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with one (1) year of experience; or PhD in data science, machine learning, computer science, statistics, or related highly-quantitative discipline.
  • Willingness to complete modest travel to various locations to support the SEI's overall mission.
  • You will be subject to a background check and must be able obtain and maintain a U.S. Department of War security clearance.

Knowledge, Skills and Abilities:
  • Experience in predictive modeling, data science, and/or AI & machine learning
  • Deep understanding of statistical modeling techniques and advanced data analytics
  • Proficient with at least one mathematical/statistical programming package (e.g., R, python numpy/scipy/pandas/polars, MATLAB, etc.)
  • Innovative and inquisitive with ability to imagine novel analytical solutions to problems Thrives in a multi-disciplinary environment
  • Strong communication skills
  • Expertise in one or more of the following:
  • Recommendation systems
  • Time-series forecasting (Prophet, NeuralProphet, Chronos, Lag-Llama, etc.)
  • NLP / LLMs (fine-tuning, RAG, evaluation, prompt engineering)
  • Causal inference / uplift modeling / synthetic controls
  • Modern ML frameworks: LightGBM/XGBoost, CatBoost, PyTorch,JAX, TensorFlow)
  • LLMs / agentic workflows (LangChain/LlamaIndex/Haystack)
  • Experience deploying models (FastAPI, Triton, KServe, SageMaker, Vertex AI, or similar)
  • Experience working with big data (Spark, Trino, Snowflake, BigQuery, Databricks)

Desired Experience:
  • Experience in cybersecurity and privacy is a plus is a plus
  • Experience in U.S. Government work and/or with FFRDCs, UARCs an National Labs is a plus
  • Demonstrated ability to learn new concepts and grow into new areas of work

Location
Arlington, VA, Pittsburgh, PA
Job Function
Software/Applications Development/Engineering
Position Type
Staff - Regular
Full time/Part time
Full time
Pay Basis
SalaryMore Information:
  • Please visit "Why Carnegie Mellon" to learn more about becoming part of an institution inspiring innovations that change the world.
  • Click here to view a listing of employee benefits
  • Carnegie Mellon University is an Equal Opportunity Employer/Disability/Veteran.
  • Statement of Assurance

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