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Data Scientist Ml Engineer Jobs (NOW HIRING)

Judge Group, Inc.

Data Scientist/ ML engineer

Irving, TX · On-site

$68 - $73/hr

Data Scientist / Machine Learning Engineer, GenAI We are not accepting C2C or 1099 arrangements ... Develop and evaluate ML models (e.g., Random Forest, XGBoost), including tuning and performance ...

HEB

Data Scientist - ML Engineering

San Antonio, TX · On-site

... data scientists, data engineers, and stakeholders to understand and fulfill their infrastructure needs. Stays updated with the latest technologies and best practices in ML infrastructure ...

Xforia, Inc.

ML engineer

Bentonville, AR · On-site

... right data science skills with problem solving, research and framing into ML problems. o 4 plus ... engineers. • The person should be able to explain his or her work and be able to go through ...

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Data Scientist Ml Engineer information

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$243.5K

How much do data scientist ml engineer jobs pay per year?

As of Jul 1, 2026, the average yearly pay for data scientist ml engineer in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What is the difference between Data Scientist Ml Engineer vs Data Analyst?

AspectData Scientist ML EngineerData Analyst
Required SkillsProgramming (Python, R), Machine Learning, Data ModelingData Visualization, SQL, Basic Statistics
Work EnvironmentDeveloping ML models, deploying algorithms, coding-intensiveData reporting, dashboard creation, data interpretation
Common Industry UsageTech, Finance, Healthcare, E-commerceRetail, Marketing, Business Services

While Data Scientist ML Engineers focus on building and deploying machine learning models using programming and advanced analytics, Data Analysts primarily interpret data through visualization and reporting to support business decisions. Both roles require strong analytical skills, but ML Engineers have a heavier emphasis on coding and model deployment, whereas Data Analysts focus on data interpretation and communication.

What are Data Scientists and ML Engineers?

Data Scientists and Machine Learning (ML) Engineers are professionals who use data, algorithms, and computational techniques to extract insights and build predictive models. Data Scientists focus on analyzing data, discovering patterns, and generating actionable insights, often using statistical and machine learning methods. ML Engineers, on the other hand, specialize in designing, developing, and deploying machine learning models into production environments, ensuring they are scalable and efficient. Both roles require strong programming skills, knowledge of mathematics and statistics, and familiarity with data processing tools. Together, they help organizations make data-driven decisions and automate processes using advanced analytics.

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

To thrive as a Data Scientist/Machine Learning Engineer, you need strong statistical analysis, programming skills (typically in Python or R), and a solid understanding of machine learning algorithms, often backed by a degree in computer science, mathematics, or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms like AWS or Azure, along with relevant certifications, is highly valuable. Critical thinking, problem-solving abilities, and effective communication help you interpret complex data and collaborate with cross-functional teams. These skills ensure you can build robust models, extract actionable insights, and drive data-driven decisions within organizations.

How do Data Scientist ML Engineers typically collaborate with other teams within an organization?

Data Scientist ML Engineers often work closely with cross-functional teams, including data engineers, product managers, software developers, and business analysts. They collaborate to understand business objectives, gather and preprocess data, develop machine learning models, and integrate solutions into production environments. Effective communication is essential, as they must translate complex technical concepts into actionable insights for stakeholders. This collaborative environment fosters innovation and ensures that machine learning solutions are aligned with organizational goals.
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Data Scientist Ml Engineer jobs near you
Infographic showing various Data Scientist Ml Engineer job openings in the United States as of June 2026, with employment types broken down into 64% Full Time, 32% Part Time, 1% Temporary, 2% Contract, and 1% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.
Data Scientist / ML Engineer

Data Scientist / ML Engineer

KSA Integration

Stafford, VA • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 27 days ago

Job description

Description:

KSA Integration is a Service-Disabled Veteran-Owned Small Business (SDVOSB) that provides business and management solutions through three core capabilities: (1) data analytics, (2) comprehensive veterans support, and (3) business process improvement. We are a rapidly growing government contractor that has built a reputation on focused customer service, on-time performance, and continuous improvement. To demonstrate this, KSA has been awarded the Inc. Best Workplaces, a prestigious list of businesses recognized for value placed on company culture, standout worker benefits, and the prioritization of employee well-being every year from 2019 to 2025. KSA also earned recognition on the Best for Vets List by Military Times from 2019 to 2025 and garnered the Department of Labor “Hire Vets” Platinum Medallion Award from 2021 to 2025.


Position Overview: KSA Integration is seeking a Data Scientist / ML Engineer to support the Marine Corps Logistics Plans (LP) Division’s data management, analytics, and artificial intelligence initiatives. This role directly supports Data Management & Analytics and AI Capability Development. You will design and deploy AI/ML solutions that transform how the Marine Corps manages logistics data, predicts readiness, and automates decision-making.


This Position is Contingent Upon Award


Anticipated Start Date: Summer 2026


Support Hours: Applicant shall be available during core work hours as established by the Government customer.

Benefits:

  • Medical, Dental, Vision (82% of employees’ premiums paid by the company, 25% towards dependents)
  • HSA / FSA Medical Plans
  • PTO
  • Flexible Work Environment and Encourage Work/Life Balance
  • 401K with Company Match
  • Observes all federal holidays
  • Professional Development/Tuition Reimbursement Program
  • Annual Career Development Process

Job Type: Full-time/Exempt

Location: Pentagon / National Capital Region (Hybrid)

Clearance Required: Active Secret

Travel Requirement: Approximately 10%


Position Responsibilities:

  • Design, develop, and deploy machine learning models and AI solutions for Marine Corps logistics applications.
  • Build predictive models for readiness forecasting, supply chain optimization, and maintenance planning.
  • Develop and maintain data pipelines, dashboards, and analytics platforms for enterprise logistics data.
  • Integrate AI/ML solutions into existing Marine Corps logistics systems and workflows.
  • Collaborate with government stakeholders to define data management goals and analytics strategies.
  • Conduct statistical analysis on complex datasets to identify trends, patterns, and actionable insights.
  • Support data governance frameworks, including data quality, privacy, security, and accessibility standards.
  • Develop best practices documentation for ML systems and train government users on AI tools.
  • Work within secure DoW computing environments (NIPR/SIPR).


Requirements:


  • 5+ years of experience in data science, machine learning, or AI engineering.
  • Proficiency in Python, R, or equivalent — hands-on experience with TensorFlow, PyTorch, scikit-learn, or similar ML frameworks.
  • Experience building and deploying ML models in production environments.
  • Strong skills in data engineering: SQL, data pipelines, ETL processes, and cloud/on-prem data platforms.
  • Experience with data visualization tools (Tableau, Power BI, Matplotlib, Plotly).
  • Familiarity with DoW data environments, ADVANA, or military logistics data systems a strong plus.
  • Experience with the Torch.AI Nexus platform or UNACORN analytics environment a plus.
  • Understanding of responsible AI principles, model governance, and DoW AI ethics frameworks.
  • BA/BS in Computer Science, Data Science, Statistics, Mathematics, or related field required; MS preferred.

Preferred Skills/Experience:

  • Prior work experience supporting the Marine Corps programs.

KSA Integration is an equal opportunity employer.

Apply