1

Freelance Data Scientist Machine Learning Jobs (NOW HIRING)

Why this Role is Different Most Data Science roles currently on the market are focused on optimizing ad clicks or slightly improving recommendation engines. This isn't that. At Nelo, your models are ...

This is an exciting Senior Data Scientist/Machine Learning opportunity to have a real impact and be a large fish in a small pond! As a Senior Data Scientist at, you will: * Develop natural language ...

Data Scientist II (Machine Learning) On Site: Norco, CA Job Summary We are seeking a talented and driven mid-level Data Scientist to join our evolving and dynamic team. In this role, you will apply ...

Essential Skills & Experience * 5+ years of expertise in data science or engineering, specifically building and deploying predictive machine learning models. * Proficiency in Python and SQL for data ...

Essential Skills & Experience * 5+ years of expertise in data science or engineering, specifically building and deploying predictive machine learning models. * Proficiency in Python and SQL for data ...

Machine Learning Data Scientist

Westminster, CO · On-site +1

$122.64K - $165.47K/yr

Essential Skills & Experience * 5+ years of expertise in data science or engineering, specifically building and deploying predictive machine learning models. * Proficiency in Python and SQL for data ...

next page

Showing results 1-20

Freelance Data Scientist Machine Learning information

See salary details

$37.5K

$122.7K

$196.5K

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

As of May 30, 2026, the average yearly pay for freelance 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 the difference between Freelance Data Scientist Machine Learning vs Freelance Data Analyst?

AspectFreelance Data Scientist Machine LearningFreelance Data Analyst
Required SkillsAdvanced statistical analysis, machine learning, programming (Python, R)Data cleaning, visualization, basic statistical analysis
Tools & TechnologiesTensorFlow, scikit-learn, Jupyter, cloud platformsExcel, Tableau, SQL
Work EnvironmentProject-based, consulting, remote or client sitesRemote, freelance consulting, client reports
Industry UsageTech, finance, healthcare, e-commerceMarketing, retail, finance, healthcare

Freelance Data Scientist Machine Learning professionals focus on developing predictive models and algorithms using advanced techniques, often requiring programming and statistical expertise. Freelance Data Analysts handle data interpretation, visualization, and reporting, typically with less technical complexity. Both roles are in high demand but differ in skill level, tools, and project scope.

More about Freelance Data Scientist Machine Learning jobs
What cities are hiring for Freelance Data Scientist Machine Learning jobs? Cities with the most Freelance Data Scientist Machine Learning job openings:
What are the most commonly searched types of Data Scientist Machine Learning jobs? The most popular types of Data Scientist Machine Learning jobs are:
What states have the most Freelance Data Scientist Machine Learning jobs? States with the most job openings for Freelance Data Scientist Machine Learning jobs include:
Infographic showing various Freelance Data Scientist Machine Learning job openings in the United States as of May 2026, with employment types broken down into 100% Part Time. Highlights an 94% Physical, and 6% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.
Data Scientist AI & Machine Learning Innovation *** Direct End Client ***

Data Scientist AI & Machine Learning Innovation *** Direct End Client ***

Projas Technologies, LLC

Mountain View, CA

Other

Posted 11 hours ago


Job description

<>Overview

We re seeking a visionary data scientist to lead the evolution of AI-driven recommendation systems and monetization strategies. This role combines technical leadership, strategic thinking, and hands-on expertise in machine learning and generative AI to deliver transformative solutions at scale.

<>Key Responsibilities
  • Architect and implement advanced machine learning systems that power intelligent recommendations and personalized experiences.
  • Define and execute a forward-looking technical vision for AI capabilities, including generative AI and agent-based systems.
  • Collaborate with engineering, product, and analytics teams to align technical strategy with business objectives.
  • Design and optimize large-scale AI platforms, ensuring scalability, reliability, and operational excellence.
  • Stay ahead of emerging trends in AI, identifying opportunities and risks to guide innovation and maintain competitive advantage.
  • Mentor and guide data scientists and engineers, fostering best practices and technical excellence.
  • Communicate complex technical concepts clearly to both technical and non-technical stakeholders.
<>Required Qualifications
  • MS or PhD in Computer Science, Machine Learning, Data Science, or related field.
  • 10+ years of experience in data science, software engineering, or AI systems architecture.
  • Proven track record of building and scaling machine learning systems for real-world applications.
  • Strong programming skills in Python, Java, or C++.
  • Expertise in designing next-generation AI solutions, including generative AI and semantic search.
  • Exceptional communication and leadership skills, with the ability to influence cross-functional teams.
<>Preferred Qualifications
  • Experience in ad technology or monetization strategies.
  • Background in developing generative AI capabilities and supporting infrastructure.
  • Ability to thrive in fast-paced, large-scale environments.

data scientist, machine learning, AI, generative AI, recommendation systems, semantic search, knowledge graph, Python, Java, C++, big data, ETL, ad tech, monetization, data architecture, AI systems, ML pipelines, predictive modeling, deep learning, cloud computing, distributed systems, operational excellence, leadership, mentoring, innovation