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Data Science Jobs in Washington, UT (NOW HIRING)

micro1 AI

Medical Writing Manager

Saint George, UT · Remote

$50 - $80/hr

... data. * Exceptional written and verbal communication skills, especially in providing structured, actionable feedback on clinical content. * Advanced degree in life sciences, pharmacy, or medicine ...

micro1 AI

Medical Billing Specialist

Saint George, UT · Remote

$50 - $80/hr

... data. * Exceptional written and verbal communication skills, especially in providing structured, actionable feedback on clinical content. * Advanced degree in life sciences, pharmacy, or medicine ...

Datavant

Area Health Information Specialist I

Saint George, UT · On-site

$93K - $94K/yr

... data solutions for organizations across the healthcare ecosystem - including providers, health plans, researchers, and life sciences companies. From fulfilling a single patient's request for their ...

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Showing results 21-40

All JobsData Science JobsData Science Jobs in Washington, UT

Data Science information

See Washington, UT salary details

$34.1K

$111.5K

$178.5K

How much do data science jobs pay per year?

As of Aug 9, 2026, the average yearly pay for data science in Washington, UT is $111,478.00, according to ZipRecruiter salary data. Most workers in this role earn between $89,500.00 and $123,500.00 per year, depending on experience, location, and employer.

Is a data scientist in high demand?

Yes, data scientists are in high demand across many industries due to the increasing reliance on data-driven decision making. The role requires skills in programming, statistics, and machine learning, and job growth is expected to continue as organizations expand their data capabilities.

What are the key skills and qualifications needed to thrive as a data scientist, and why are they important?

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

What does a data scientist do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.
More about Data Science jobs
What are popular job titles related to Data Science jobs in Washington, UT? For Data Science jobs in Washington, UT, the most frequently searched job titles are:
What cities near Washington, UT are hiring for Data Science jobs? Cities near Washington, UT with the most Data Science job openings:
Data Science jobs near you
Infographic showing various Data Science job openings in Washington, UT as of August 2026, with employment types broken down into 100% Full Time. Highlights an 80% In-person, 4% Hybrid, and 16% Remote job distribution, with an average salary of $111,478 per year, or $53.6 per hour.

Medical Writer / Clinical Document Author

micro1 AI

Saint George, UT • Remote

$50 - $80/hr

Part-time

Posted 5 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.

Apply