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Remote Data Science R Jobs in Utah (NOW HIRING)

You'll work closely with Product Design, Engineering, and Data Science to turn customer needs into ... R.T. of Hirevue. They are: Hero for our Customers, Enjoy the Journey, Always do the Right Thing ...

Title: Sales Ops Data Analyst In Office /Remote: /Hybrid Exempt / Non-exempt Based: Manila ... Use Python/R and VBA to create and send regular performance reports, focusing on backlog/billing ...

... R. AI-assisted development is the default form factor for the team. Most of the code we ship is ... This is a remote role that is part of the Finance department and reports to the Director of Data ...

Work with dispatch systems support to ensure the remote data requirements are incorporated into the ... Bachelor's Degree Electrical Engineering, Computer Science, Information Technology, or related ...

Work with dispatch systems support to ensure the remote data requirements are incorporated into the ... Bachelor's Degree Electrical Engineering, Computer Science, Information Technology, or related ...

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Remote Data Science R information

What is the difference between Remote Data Science R vs Remote Data Analyst?

AspectRemote Data Science RRemote Data Analyst
Required SkillsStatistical analysis, R programming, data modeling, machine learningData visualization, basic statistical analysis, Excel, SQL
CertificationsR certifications, data science certificates, possibly advanced degreesData analysis certifications, Excel, SQL courses
Work EnvironmentCollaborative teams, research projects, data science platformsReporting, dashboards, business insights
Industry UsageTech, finance, healthcare, research institutionsMarketing, retail, finance, operations

Remote Data Science R roles focus on advanced statistical modeling and machine learning using R, often requiring specialized certifications and working on complex data projects. Remote Data Analysts typically handle data reporting, visualization, and basic analysis to support business decisions. While both roles involve data handling, Data Science R positions demand deeper technical expertise and programming skills.

What is a remote data science R?

Remote Data Science R jobs are positions that involve using the R programming language to analyze and interpret data, build statistical models, and generate insights, all while working from a remote location. These roles typically require strong skills in data manipulation, visualization, and statistical analysis using R. Professionals in these positions may work for companies in various industries, collaborating with teams online and leveraging cloud-based tools. Remote Data Science R jobs offer flexibility, allowing individuals to work from home or anywhere with a reliable internet connection.

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

To thrive as a Remote Data Scientist, you need strong analytical skills, expertise in statistics, programming (Python or R), and typically a degree in data science, computer science, or a related field. Familiarity with data analysis tools, machine learning frameworks (like TensorFlow or scikit-learn), and cloud platforms (such as AWS or Google Cloud) is commonly required. Outstanding problem-solving, self-motivation, and effective virtual communication skills help you excel in remote environments. These abilities are essential for deriving actionable insights from data and collaborating efficiently across distributed teams.

How do remote data science R professionals typically collaborate with cross-functional teams while working from different locations?

Remote Data Science R professionals often use a combination of communication platforms (like Slack, Microsoft Teams, or Zoom) and project management tools (such as Jira or Trello) to stay connected with colleagues in engineering, product management, and business analysis. Sharing code and models through version control systems (like Git) and documenting workflows in shared repositories helps maintain transparency and collaboration. Regular virtual meetings and presentations are crucial for aligning goals, discussing progress, and receiving feedback. This collaborative approach ensures that data-driven insights effectively support organizational objectives, even in a distributed work environment.
What are popular job titles related to Remote Data Science R jobs in Utah? For Remote Data Science R jobs in Utah, the most frequently searched job titles are:
What cities in Utah are hiring for Remote Data Science R jobs? Cities in Utah with the most Remote Data Science R job openings:

R&D Data Scientist

Hexcel Corporation

Salt Lake City, UT • On-site, Remote

Full-time

Re-posted 11 days ago


Hexcel rating

7.5

Company rating: 7.5 out of 10

Based on 19 frontline employees who took The Breakroom Quiz


Job description

With our strong investment in research and development and our culture of continuous improvement, Hexcel is the industry leader in the manufacturing of advance composite materials, including carbon fiber, woven reinforcements, resins, prepregs, honeycombs and engineered core and composite structures. We invite you to join the Hexcel team at various manufacturing sites, sales offices and R&D centers around the globe. Become a part of the "strength within."

Hexcel is currently seeking aResearch and Development Data Scientistfor ourSalt Lake City, UT, USA. This person will lead the development and deployment of digital twin technologies that accelerate material, process, and product innovation.This role will focus on building virtual representations of manufacturing processes, materials, and products using advanced analytics, machine learning, physics-based modeling, and AI. The successful candidate will bridge physical experimentation and digital simulation to improve process performance, reduce development cycles, and support next-generation composite material technologies.

The selected individual will be responsible for but not limited to the following obligations:

  • Lead the design, development, validation, and deployment of digital twins for manufacturing processes, material systems, and product development programs.
  • Develop hybrid modeling approaches that combine physics-based models, first-principles engineering, machine learning, and statistical methodologies.
  • Integrate sensor, process, quality, and operational data into digital twin frameworks to improve predictive capabilities and decision-making.
  • Design and implement advanced AI, machine learning, and analytics solutions that enhance model accuracy, process control, and product performance.
  • Collaborate with scientists, engineers, technicians, and manufacturing teams to translate physical system behavior into scalable digital twin architectures.
  • Support experimentation strategies, including Design of Experiments (DOE), active learning, and closed-loop optimization to continuously improve digital twin performance.
  • Develop simulation environments for evaluating process changes, material innovations, and manufacturing outcomes before physical implementation.
  • Establish model governance practices including validation, uncertainty quantification, monitoring, and lifecycle management of digital twin applications.
  • Communicate digital twin insights and recommendations to technical and business stakeholders to drive data-driven innovation and operational excellence.

Required Qualifications

  • Master's degree in data science, Materials Science, Chemical Engineering, Mechanical Engineering, Applied Mathematics, Physics, or a related technical discipline.
  • Minimum 2+ years of experience developing predictive models, digital twins, simulation tools, or advanced analytics solutions in an industrial environment.
  • Demonstrated experience creating and validating digital twin or virtual process models using machine learning, statistical modeling, physics-based modeling, or hybrid approaches.
  • Experience modeling complex physical, chemical, or manufacturing systems.
  • Strong analytical and problem-solving skills with the ability to connect physical processes to data-driven modeling techniques.
  • Proficiency in Python, R, or similar programming languages and associated machine learning ecosystems.
  • Experience with cloud-based data and AI platforms, preferably Microsoft Azure.
  • Strong communication skills with the ability to explain complex modeling concepts to multidisciplinary teams.
  • Eligible candidates must be a U.S. citizen.

Preferred Qualifications

  • Experience with Digital Twin platforms, Industrial IoT architectures, or digital thread initiatives.
  • Experience with Azure Digital Twins, Azure Machine Learning, Azure IoT, Microsoft Fabric, Synapse, or related Microsoft technologies.
  • Experience working with manufacturing data, process optimization, materials development, or composite materials.
  • Familiarity with ML Ops, model deployment, model governance, and continuous monitoring frameworks.
  • Experience utilizing large language models (LLMs), generative AI, or AI agents to support engineering and scientific workflows.
  • Experience applying AI and optimization techniques to material formulation or chemical composition development

Eligible candidates must be a: U.S. citizen, U.S. national, person lawfully admitted for permanent residence, temporary resident under sections 210(a) or 245(A) of the Immigration and Nationality Act, person admitted in refugee status, or person granted asylum. Hexcel (NYSE: HXL) is a global leader in advanced composites technology, a leading producer of carbon fiber, and the world leader in honeycomb manufacturing for the commercial aerospace industry.

Hexcel is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin, physical or mental disability, status as a protected veteran, or any other protected class.


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