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Data Science Machine Learning Jobs (NOW HIRING)

Merican

Data Science & Machine Learning Engineer

$117K - $140K/yr

Senior Data Science & Machine Learning Engineer Location: Remote, USA (Client Location ZIP: 01730) Duration: 6 Months Contract to Hire We are seeking an experienced Senior Data Science & Machine ...

Mars Technominds Inc

Data Science Architect

Mckinney, TX · On-site

$59 - $76/hr

The ideal candidate will have strong expertise in Data Science, Machine Learning, Python, SQL, cloud technologies, data architecture, and MLOps, with the ability to translate complex business and ...

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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 1, 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.
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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 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 Science & Machine Learning Engineer

Merican

Remote

$117K - $140K/yr

Contractor

Re-posted 19 days ago

Job description

Hiring: Senior Data Science & Machine Learning Engineer
Location: Remote, USA (Client Location ZIP: 01730)
Duration: 6 Months Contract to Hire
We are seeking an experienced Senior Data Science & Machine Learning Engineer to design, build, and deploy scalable data-driven and AI-powered solutions.
Required Skills & Responsibilities:
  • 5+ years of experience in Data Engineering, Machine Learning Engineering, or related fields.
  • Strong programming expertise in Python (Pandas, NumPy, PySpark, etc.).
  • Design, develop, deploy, and maintain production-ready Machine Learning models.
  • Experience with ML model training, deployment, monitoring, and observability.
  • Hands-on experience with Deep Learning frameworks such as TensorFlow and PyTorch.
  • Build robust data pipelines, feature engineering workflows, and experimentation platforms.
  • Experience working with LLMs, Generative AI, MLOps, and modern AI architectures.
  • Familiarity with CI/CD pipelines, Git, and software engineering best practices.
  • Ability to mentor junior engineers and contribute to technical design decisions.

Preferred Qualifications:
  • Bachelor's degree in Computer Science, Data Science, Engineering, Statistics, Mathematics, or related field.
  • Master's degree or PhD is a plus.
  • Strong analytical, problem-solving, and communication skills.

Interested candidates, please share your updated resume along with your contact details and availability.
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About Merican

Sourced by ZipRecruiter

Merican is a IT Service consulting firm, specialized in Digital adoption and Business automation. With our diverse collection of skilled and committed consultants, technology companies, businesses and digital experts, we provide our subject expertise and our unique client service approach, a best-in-class global model of delivery suited to the business demands of our clients. We ensure that we implement future-oriented solutions for our clients via investments in people, solutions, technologies, competencies and infrastructure.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Columbia , MD, US

Year founded

2020

Social media

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