ZipRecruiter

Log In

1

Data Science Jobs in Washington, UT (NOW HIRING)

beatBread

AI Engineer

Saint George, UT · On-site

$50K - $90K/yr

Collaborate with data scientists and engineers to optimize model performance and reliability * Implement, monitor, and improve model training processes, including domain-specific custom training

beatBread

AI Engineer

Saint George, UT · On-site

Collaborate with data scientists and engineers to optimize model performance and reliability * Implement, monitor, and improve model training processes, including domain-specific custom training

Civil Science

Field Engineer

Saint George, UT · On-site

Civil Science is growing our construction team in Utah and is seeking a Field Engineer to support ... Participating in field inspections, data collection, and construction verification * Supporting ...

Wipro Limited

Data Analytics L1(CONTRACT)

Santa Clara, UT · On-site

$60K - $148K/yr

Data Analytics L1(CONTRACT) City: Santa Clara State/Province: California Posting Start Date: 8/18/26 Wipro Limited (NYSE: WIT, BSE: 507685, NSE: WIPRO) is a leading technology services and consulting ...

next page

Showing results 1-20

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 31, 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.

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 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.

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 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.

Is a data scientist in high demand?

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 jobs can a data scientist do?

A data scientist can work in roles such as data analyst, machine learning engineer, data engineer, or business intelligence analyst. These roles involve analyzing large datasets, developing predictive models, and using tools like Python, R, and SQL to support decision-making across various industries.
More about Data Science jobs

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 1% As Needed, 78% Full Time, 19% Part Time, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $111,478 per year, or $53.6 per hour.

AI Engineer

beatBread

Saint George, UT • On-site

$50K - $90K/yr

Full-time

Re-posted 2 days ago

Job description

About The Role
As an AI Engineer, you will design, build, and deploy sophisticated AI solutions that drive innovation and strategic impact across the organization. Collaborating closely with cross-functional teams, you will develop and optimize machine learning models, refine data pipelines, and harness emerging AI technologies such as ChatGPT and OpenAI APIs. This role offers the opportunity to shape and implement AI-driven strategies, leveraging your expertise in Python, SQL, Docker, AWS, and custom ML training techniques.
Essential Duties and Responsibilities
  • Lead the end-to-end development, testing, and deployment of AI and ML models
  • Architect and maintain scalable data pipelines using Python, SQL, and AWS services
  • Integrate and fine-tune ChatGPT and OpenAI APIs to meet specific business needs
  • Build and manage containerized environments and workflows with Docker
  • Collaborate with data scientists and engineers to optimize model performance and reliability
  • Implement, monitor, and improve model training processes, including domain-specific custom training
  • Advise on and adopt new AI frameworks and best practices to enhance the organization's AI capabilities
  • Troubleshoot and resolve performance and security issues related to AI systems

Qualifications and Skills
  • Bachelor's degree in Computer Science, Data Science, Engineering, or related field, or equivalent experience.
  • 4-8 years of experience in AI engineering, data science, software engineering, software development, or related roles.
  • Proficiency in Python for data manipulation, scripting, and model development
  • Solid understanding of SQL for data querying, management, and optimization
  • Hands-on experience with Docker for containerization and deployment
  • Familiarity with ChatGPT, OpenAI APIs, and other large language models
  • Strong knowledge of machine learning fundamentals (supervised/unsupervised learning, model tuning, evaluation)
  • Experience working with AWS (e.g., S3, EC2, Lambda) for cloud-based solutions
  • Ability to collaborate effectively with cross-functional stakeholders
  • Proven track record of learning and adapting to emerging AI technologies and tools

Physical Requirements
  • Flexible to work additional hours as needed to meet project deadlines.
  • Ability to sit and work at a computer for extended periods.
  • Occasional lifting of equipment or materials may be required, but not exceeding 20 pounds.
  • Ability to communicate effectively in person, over the phone, and through digital channels.

Apply