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Data Scientist Machine Learning Jobs (NOW HIRING)

Koantek

Data Scientist

Chandler, AZ · On-site

Data Scientist / Senior Data Scientist We are seeking a highly skilled Data Scientist with strong ... Build and optimize machine learning models for classification, regression, predictive analytics ...

Koantek

Data Scientist

Chandler, AZ

Data Scientist / Senior Data Scientist We are seeking a highly skilled Data Scientist with strong ... Build and optimize machine learning models for classification, regression, predictive analytics ...

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

As of Jun 25, 2026, the average yearly pay for data scientist 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 a Data Scientist Machine Learning job?

A Data Scientist specializing in Machine Learning (ML) uses statistical methods, algorithms, and computational power to analyze data and create predictive models. They work with large datasets to identify patterns, train machine learning models, and improve decision-making processes. Responsibilities often include data cleaning, feature engineering, model selection, and performance evaluation. They may collaborate with engineers and business teams to deploy models in real-world applications. Strong skills in programming (Python, R), ML frameworks (TensorFlow, Scikit-learn), and data visualization are essential.

What are the key skills and qualifications needed to thrive in the Data Scientist Machine Learning position, and why are they important?

To excel as a Data Scientist Machine Learning, you need a strong proficiency in statistics, programming (typically Python or R), and a solid understanding of machine learning algorithms, usually backed by a degree in computer science, mathematics, or a related field. Familiarity with tools such as TensorFlow, scikit-learn, SQL databases, and cloud platforms, as well as certifications in data science or machine learning, is commonly expected. Analytical thinking, problem-solving skills, and effective communication are vital soft skills in this profession. These qualifications combine to drive impactful insights and enable the successful development and deployment of machine learning models in business environments.

Is ML a high paying job?

Data Scientist Machine Learning roles are generally well-paid due to the specialized skills required, such as programming in Python or R and knowledge of algorithms. Salaries vary by experience, location, and industry, but they tend to be higher than average for tech roles, reflecting the demand for expertise in machine learning and data analysis.

Is 40 too late for data science?

Data scientists can enter the field at any age, including 40 or older, as success depends on skills, experience, and continuous learning. Many professionals transition into data science later in their careers by acquiring relevant knowledge in programming, statistics, and machine learning tools. Age is less important than demonstrated expertise and the ability to adapt to evolving technologies.

Which 5 jobs will survive AI?

Data Scientist Machine Learning roles are likely to persist as they require advanced analytical skills, domain expertise, and the ability to interpret complex models. Jobs that involve creative thinking, emotional intelligence, and tasks requiring human judgment—such as healthcare professionals, educators, and skilled trades—are also expected to remain resilient despite AI advancements.

What are the typical day-to-day responsibilities of a Data Scientist Machine Learning?

On a typical day, a Data Scientist specializing in Machine Learning might gather and preprocess data, design and implement machine learning models, and evaluate their performance to solve real-world problems. They often collaborate with data engineers, software developers, and business stakeholders to translate business objectives into technical solutions and integrate models into existing systems. Other responsibilities can include visualizing data insights, conducting experiments to tune algorithms, and staying current with new developments in the field. The work is highly collaborative and iterative, requiring clear communication with various teams to ensure project goals are met efficiently.

Do data scientists do machine learning?

Yes, data scientists often use machine learning techniques to analyze data, build predictive models, and extract insights. Proficiency in programming languages like Python or R and understanding of algorithms are essential skills for applying machine learning in their work.
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Data Scientist Machine Learning jobs near you
Infographic showing various Data Scientist Machine Learning job openings in the United States as of June 2026, with employment types broken down into 25% Full Time, 25% Part Time, and 50% 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.
Data Scientist - Machine Learning and AI

Data Scientist - Machine Learning and AI

Savannah River National Laboratory

Aiken, SC • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 3 days ago

Job description


Savannah River National Laboratory is seeking a highly motivated and self-starting AI (artificial intelligence) and machine learning researcher to join our team in creating and maintaining large-language model research tools, especially for cybersecurity data. The successful candidate will have strong experience in Python, AI, and cybersecurity, with a focus on developing and maintaining high-quality code using unit testing, continuous integration, and deep learning models and libraries. The ideal candidate will be a solid researcher (PhD preferred), an independent worker, a good communicator, and a team player with a strong ability to write and document his or her work.
Responsibilities
  • Develop and maintain large-language model research tools for cybersecurity data using Python, Huggingface models, and Pytorch libraries or other equivalent state-of-the-art technology
  • Design and implement unit tests and continuous integration pipelines to ensure high-quality code
  • Collaborate with team members to develop and maintain research tools and software applications
  • Write and maintain technical documentation for research tools and software applications
  • Participate in code reviews and contribute to the improvement of the overall codebase
  • Develop and maintain strong understanding of cybersecurity concepts and threats
  • Collaborate in writing proposals for external sponsors, Laboratory Directed Research and Development (LDRD) projects, and other funding opportunities
  • Stay up-to-date with the latest developments in AI, cybersecurity, and large-language models

Typical Tools and Technologies:
  • Python libraries: NumPy, pandas, SciKit-Learn, Pytorch, TensorFlow
  • Data visualization tools: Plotly/Dash, Kibana, Matplotlib, Seaborn
  • Machine learning frameworks: SciKit-Learn, Pytorch, TensorFlow
  • Operating Systems: RHEL, Linux
  • Batch processing tools: PBS, SLURM
  • Version control systems: Git
  • Agile development methodologies: Scrum, Kanban
  • Others as the technology stack changes

Qualifications
Minimum Qualifications:
  • Bachelor's degree in Computer Science, Cybersecurity, or related field and 4-6 years of experience in software development, preferably in a research environment
  • For ability to obtain and maintain a security clearance, US Citizenship is Legally Required
  • Strong experience in Python programming, including experience with AI and machine learning libraries (e.g. Pytorch, TensorFlow, scikit-learn)
  • Experience with deep learning models and libraries, particularly Huggingface, Pytorch, etc.
  • Strong understanding of cybersecurity concepts and threats
  • Experience with unit testing and continuous integration (e.g. Jenkins, GitHub, or others)
  • Excellent communication and teamwork skills
  • Ability to write and document technical work
  • Experience with version control systems (e.g. Git)
  • Familiarity with Agile development methodologies
  • Self-motivated and able to work independently
  • Experience with Red Hat Enterprise Linux (RHEL) or similar Linux distributions
  • Experience with batch processing tools such as PBS or SLURM
  • Familiarity with data engineering and curation principles and practices
  • Experience with data visualization tools such as Plotly/Dash, Kibana, or similar tools

Preferred Qualifications:
  • Experience with machine learning primitives and ability to choose the right approach for a given problem (e.g. decision trees, random forests, deep learning)
  • Experience with natural language processing (NLP) techniques and libraries (e.g. NLTK, spaCy)
  • Familiarity with containerization (e.g. Docker)
  • Experience with cloud-based platforms (e.g. AWS, Azure)
  • Certification in cybersecurity or a related field (e.g. CompTIA Security+, CISSP)
  • Experience with proposal writing and research funding opportunities
  • Masters Degree in Computer Science, Cybersecurity, or related field

About Us
"We put science to work!"
Savannah River National Laboratory (SRNL) is a multi-program laboratory applying state of the art science and practical, high-value, cost-effective solutions to complex technical problems to protect the nation. Located at the U.S. Department of Energy's (DOE) Savannah River Site (SRS) in Aiken SC, the laboratory develops and deploys innovative technologies to address some of the nation's environmental, energy, and national security challenges.
Battelle Savannah River Alliance (BSRA) is constantly assessing trends to provide the best possible benefits to our workforce. We also negotiate cost effective premiums that will meet the needs of our evolving workforce.
Some of the *Benefits offered to employees include:
*Benefits vary based upon employment status
  • Highly competitive Medical, Dental, and Vision options including HSA options with company provided seed
  • Short- & Long-Term Disability (company paid)
  • Life Insurance Non-Contributary 1X salary (company paid)
  • AD&D Non-contributary 1x salary (company paid)
  • Savings & Investment plan:
    • Qualified Non-Elective Company Contribution of 5% each pay period with immediate vesting
    • Company match 50 cents/dollar up to 8% (5 yrs. vesting in company match)
  • Contributory Life Insurance up to 5x Salary with $1M Cap
  • Contributory AD&D (employee, spouse and children)
  • Paid Time Off
  • Employee Assistance Plan
  • SRNL offers a competitive relocation package to ease the transition process. Domestic and international relocation assistance is available for certain positions.

For more information about our benefits, working here, and living here, visit the "About" tab at www.srnl.doe.gov.
BSRA is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, or protected veteran status. BSRA is also committed to making our workplace accessible to individuals with disabilities and will provide reasonable accommodations, upon request, for individuals to participate in the application and hiring process. Please email us at SRNLRecruiting@srnl.doe.gov with any questions regarding the hiring process or to request an accommodation.
About the Team
The Global Security Directorate (GSD) of SRNL provides a team focused on staff development and infrastructure upgrades for nuclear reprocessing science and technology programs at SRNL. GSD is growing its support of its critical NNSA nonproliferation portfolios and is building its teams to support these enduring programs. GSD is looking for people who can use their talents and experience to help build state of the art business programs as SRNL continues to use it diverse creative staff to deliver the highest quality programs to its customer.

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