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Remote Data Scientist Machine Learning Jobs in Yuma, AZ

Medical Writing Manager

Yuma, AZ · Remote

$50 - $80/hr

Remote micro1 is engaging Medical Writers / Clinical Document Authors to participate in a customer ... Evaluate scientific accuracy in narrative sections such as efficacy, safety summaries, discussion ...

Salesforce Developer

Yuma, AZ · On-site +1

$55 - $72.75/hr

Hybrid / Remote / On-site Location: [Location] Job Summary We are looking for an experienced ... Salesforce Integration * Salesforce Data Model * Git / Version Control Secondary Skills

Biostatistician

Yuma, AZ · Remote

$60 - $100/hr

Remote micro1 is engaging Biostatisticians to contribute to a customer's advanced project in AI ... Source, construct, and curate authentic datasets including trial data, patient records, and ...

Director of Biostatistics

Yuma, AZ · Remote

$60 - $100/hr

Remote micro1 is engaging Biostatisticians to contribute to a customer's advanced project in AI ... Source, construct, and curate authentic datasets including trial data, patient records, and ...

IAM Automation Engineer

Yuma, AZ · Remote

$90K - $110K/yr

Remote in Arizona, occasional in-person meetings will occur Job Type: Full Time Compensation: $90 ... You will help ensure secure, efficient access to systems and data by developing scalable workflows ...

Showing results 21-32

Remote Data Scientist Machine Learning information

See Yuma, AZ salary details

$37.1K

$121.5K

$194.4K

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

As of Aug 22, 2026, the average yearly pay for remote data scientist machine learning in Yuma, AZ is $121,455.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,500.00 and $134,600.00 per year, depending on experience, location, and employer.

What does a remote data scientist specializing in machine learning do?

A Remote Data Scientist specializing in Machine Learning uses advanced statistical techniques and programming skills to analyze large datasets and build predictive models, all while working from a remote location. They design, develop, and deploy machine learning algorithms to solve business problems, such as forecasting trends or automating processes. Their work often involves data cleaning, feature engineering, model selection, and collaborating with cross-functional teams to integrate these models into products or services. Remote data scientists typically use tools like Python, R, and cloud-based platforms to perform their tasks efficiently.

How do remote data scientists specializing in machine learning typically collaborate with cross-functional teams?

Remote data scientists in machine learning often work closely with product managers, engineers, and business analysts through virtual meetings, collaborative platforms, and shared documentation tools. They regularly participate in sprint planning, code reviews, and brainstorming sessions to ensure alignment with project goals. Effective communication and proactive updates are essential for overcoming the challenges of remote collaboration and maintaining project momentum. Building strong relationships with team members across different time zones helps foster innovation and ensures that machine learning solutions are well-integrated into broader business objectives.

What are the key skills and qualifications needed to thrive as a remote data scientist specializing in machine learning?

To excel as a Remote Data Scientist in Machine Learning, you need a solid background in statistics, programming (typically Python or R), and a degree in computer science, mathematics, or a related field. Familiarity with tools and frameworks such as TensorFlow, scikit-learn, PyTorch, and experience with cloud platforms like AWS or Azure are often required, along with relevant certifications. Strong problem-solving skills, effective communication, and the ability to work independently are crucial soft skills for remote collaboration and translating insights for diverse stakeholders. These competencies ensure the development of robust models, clear communication of findings, and successful project delivery in a distributed work environment.

What is the difference between Remote Data Scientist Machine Learning vs Remote Data Scientist?

AspectRemote Data Scientist Machine LearningRemote Data Scientist
Required CredentialsMaster's or PhD in Data Science, Computer Science, or related field; experience with ML frameworksSimilar educational background; may focus more on statistical analysis and data visualization
Work EnvironmentPrimarily involves developing ML models, coding in Python/R, and deploying algorithmsFocuses on data analysis, reporting, and insights generation, often with less emphasis on ML deployment
Employer & Industry UsageUsed in tech, finance, healthcare for predictive modeling and automationCommon across various industries for data analysis and business intelligence

While both roles require strong analytical skills and similar educational backgrounds, Remote Data Scientist Machine Learning specializes in developing and deploying machine learning models, whereas Remote Data Scientist focuses more on data analysis and reporting. The ML role often involves coding and algorithm development, making it more technical in nature.

What are popular job titles related to Remote Data Scientist Machine Learning jobs in Yuma, AZ?

For Remote Data Scientist Machine Learning jobs in Yuma, AZ, the most frequently searched job titles are:

What cities near Yuma, AZ are hiring for Remote Data Scientist Machine Learning jobs?

Cities near Yuma, AZ with the most Remote Data Scientist Machine Learning job openings:

Medical Writing Manager

micro1 AI

Yuma, AZ • Remote

$50 - $80/hr

Part-time

Posted 18 days ago


Job description

Role Title: Medical Writer / Clinical Document Author


Role Type: Contractor


Location: Remote


micro1 is engaging Medical Writers / Clinical Document Authors to participate in a customer’s project focused on developing advanced AI-assisted writing tools for clinical documentation. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Author and review realistic evaluation tasks based on Clinical Study Reports, DSURs, PSURs/PBRERs, and related clinical documents to inform AI tool development.
  2. Apply expert judgment to assess whether AI-generated content fulfills clinical template and structural requirements, including ICH E3 organization, section sequencing, cross-referencing, and appendix management.
  3. Evaluate scientific accuracy in narrative sections such as efficacy, safety summaries, discussion, and conclusions, distinguishing true scientific or interpretive errors from stylistic differences.
  4. Trace narrative claims to source records—tables, figures, listings, and protocols—to verify that all assertions are appropriately supported.
  5. Provide clear and structured written rationales for each assessment, enabling precise diagnosis and improvement of AI model behavior.
  6. Collaborate with project leads to refine evaluation frameworks and document best practices for clinical regulatory writing in the context of AI.


Preferred Qualifications

  1. Minimum 5 years of regulatory medical writing experience at a sponsor, CRO, or as an independent consultant.
  2. Direct experience independently authoring or leading the authoring of full Clinical Study Reports, beyond summaries or partial contributions.
  3. Fluency with ICH E3 and conventions for periodic safety documentation (ICH E2F, ICH E2C) and eCTD placement.
  4. Demonstrated ability to read and interpret TFLs and protocol documents, identifying where narrative diverges from source data.
  5. Exceptional written and verbal communication skills, especially in providing structured, actionable feedback on clinical content.
  6. Advanced degree in life sciences, pharmacy, or medicine (PhD, PharmD, MD, MSc), or equivalent depth of authoring experience.
  7. Experience across multiple clinical phases and therapeutic areas; oncology and haematology expertise is especially valued.


Join our customer's team and leverage your authoring expertise to help design the next generation of AI-assisted clinical documentation solutions. This high-bar role offers you the chance to shape how tomorrow's writing teams draft and review regulatory documents — through your expert input, judgment, and real-world experience.