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Remote Image Processing Scientist Jobs in Arizona

Sprouts Farmers Market

Data Scientist

Phoenix, AZ · Remote

Overview This is a fully remote opportunity. Sprouts is currently at the beginning of a journey to ... Provide leadership and direction to ensure processes and procedures are in place to effectively use ...

Sprouts Farmers Market

Data Scientist

Phoenix, AZ · Remote

Overview This is a fully remote opportunity. Sprouts is currently at the beginning of a journey to ... Provide leadership and direction to ensure processes and procedures are in place to effectively use ...

Agile Defense

Data Scientist - A365

Fort Huachuca, AZ · On-site +1

$85K - $95K/yr

Data Scientist - A365 Location: Remote Clearance Level: Secret, Must Have Clearance to Start ... If you would like more information about how your data is processed, please contact us.

Agile Defense

$85K - $95K/yr

Data Scientist - A365 Location: Remote Clearance Level: Secret, Must Have Clearance to Start ... If you would like more information about how your data is processed, please contact us. apply for ...

SimonMed Imaging

Remote Radiologist- Nuero

Scottsdale, AZ · Remote

$319K - $399K/yr

Collaborate with technologists to ensure optimal image quality and protocol adherence. Participate ... Strong understanding of anatomy, pathology, and radiological sciences. Excellent written and verbal ...

SMI IMAGING LLC

Remote Radiologist- Nuero

Scottsdale, AZ · On-site +1

$319K - $399K/yr

... image quality and protocol adherence. • Participate in quality assurance, peer review, and ... sciences. • Excellent written and verbal communication skills. • Ability to work efficiently in ...

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Remote Image Processing Scientist information

What are some common challenges faced by Remote Image Processing Scientists when collaborating with cross-functional teams?

Remote Image Processing Scientists often work with diverse teams, including software engineers, data scientists, and project managers. A common challenge is ensuring clear communication of complex technical concepts, especially when team members have varying levels of expertise in image processing. Additionally, aligning on project goals and integrating image processing workflows with broader system architectures can require extra coordination in a remote setting. Proactively scheduling regular meetings and using collaborative tools can help bridge these gaps and foster effective teamwork.

What is the difference between Remote Image Processing Scientist vs Remote Computer Vision Engineer?

AspectRemote Image Processing ScientistRemote Computer Vision Engineer
Required CredentialsMaster's or PhD in Computer Science, Electrical Engineering, or related fields; experience with image processing algorithmsBachelor's or higher in Computer Science or Electrical Engineering; strong programming skills in Python, C++, and experience with vision libraries
Work EnvironmentResearch-focused, often in R&D teams, developing new image processing techniquesDevelopment-focused, implementing and deploying computer vision models in products
Employer & Industry UsageTech companies, research labs, healthcare, automotiveTech firms, autonomous vehicles, robotics, security systems

While both roles involve working with visual data, the Remote Image Processing Scientist primarily focuses on research and developing new algorithms, whereas the Remote Computer Vision Engineer applies these techniques to build practical applications and systems.

What are the key skills and qualifications needed to thrive as a Remote Image Processing Scientist, and why are they important?

To thrive as a Remote Image Processing Scientist, you need a solid background in computer vision, image analysis, and strong programming skills, generally supported by a degree in computer science, electrical engineering, or a related field. Expertise in tools such as Python, MATLAB, OpenCV, and familiarity with machine learning frameworks and cloud computing platforms is typically required. Strong problem-solving abilities, self-motivation, and effective communication are important soft skills, especially when working in remote or distributed teams. These skills ensure the development of robust image processing solutions, efficient collaboration, and the ability to adapt to evolving project requirements.

What is a Remote Image Processing Scientist?

A Remote Image Processing Scientist is a professional who specializes in analyzing and interpreting images using advanced computational techniques, often working from a remote location. They process and enhance digital images, such as satellite photos, medical scans, or photographs, using algorithms and software tools. Their work may involve developing new image analysis methods, improving image quality, and extracting meaningful data for various applications like remote sensing, healthcare, or security. Remote Image Processing Scientists typically have backgrounds in computer science, engineering, or related fields, and are skilled in programming, mathematics, and data analysis.
What are popular job titles related to Remote Image Processing Scientist jobs in Arizona? For Remote Image Processing Scientist jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Remote Image Processing Scientist jobs in Arizona look for? The top searched job categories for Remote Image Processing Scientist jobs in Arizona are:
What cities in Arizona are hiring for Remote Image Processing Scientist jobs? Cities in Arizona with the most Remote Image Processing Scientist job openings:
Remote Image Processing Scientist jobs near you

Principal AI Data Scientist

MSR Technology Group

Phoenix, AZ • Remote

Full-time

Re-posted 24 days ago

Job description


Infomatics is partnered with a large retailer that is hiring a Principal AI Data Scientist on a direct hire/FTE basis near Phoenix, AZ. Can work remote. All applicants must be eligible & willing to be hired on W2.

You will lead various AI efforts involving computer vision, deep learning, and nlp in addition to other machine learning model builds. You will not only work on large scale projects to provide value to the customers but are also routinely involved in building our internal R&D capability to have an edge in the analytics industry. You will lead some of the most strategic and very complex problems.
Duties/Responsibilities:
  • Builds and validates machine learning models of high risk/reward problems utilizing large scale data from multiple data sources and methodologies.
  • Uses machine learning techniques to create data-driven solutions for various business use-cases.
  • Writes programs utilizing existing libraries and methodologies.
  • Interprets, communicates, and presents analytic results to C-Level executives and below.
  • Consistently collaborates with fellow data scientists, data engineers, business partners, project managers, cross-functional teams, key stakeholders, and other domains to drive business value.
  • Leads AI best practice sharing opportunities and knowledge of industry trends and innovations in data science.
  • Leads projects with external partners and vendors to develop solutions to meet business needs while resolving any issues that may arise.
  • Contributes to the organization's data strategy and roadmap.
  • Embeds and drives the organization with the most up-to-date AI methodology.
Qualifications:
  • Master's or PhD degree in a quantitative field with 5+ years of data science experience.
  • Applied expertise in artificial intelligence with experience applying natural language processing, computer vision (image processing), and deep leaning. Need to have the capability to leverage current mature mainstream AI application tools and methodology
  • Proficiency in machine learning with familiarity and actual applications of scikit-learn library machine learning techniques such as decision tree, gradient boosting, XGBoost, etc. for regression, classification, or segmentation problems.
  • Programming expertise in Python with familiarity with cloud environments (AWS, Databricks, etc.)
  • Ability to work with large data sets from multiple data sources
  • Ability to communicate complex analytics concepts and techniques to C-Level executives and below
  • Ability to work collaboratively with other data scientists, data engineers, multiple stakeholders across the business, and with external partners
  • Intellectual curiosity, a passion for data, and a results orientation.