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Computer Vision Data Scientist Jobs (NOW HIRING)

Tractor Zoom

Be Seen First

Senior Data Scientist

Des Moines, IA · On-site

$120K - $145K/yr

Senior Data Scientist Hybrid - West Des Moines, IA | Full-Time About Tractor Zoom We are committed ... Expertise in at least one subject area: computer vision, time series forecasting, deep learning ...

Booz Allen Hamilton

Computer Vision AI Engineer

Mclean, VA · On-site

$99K - $225K/yr

R0238504 Computer Vision AI Engineer The Opportunity: Booz Allen Hamilton is seeking an innovative ... In this role, you will leverage your expertise in artificial intelligence, data science, and ...

Technogen, Inc.

Data Scientist

Camden, NJ · Hybrid

Data Scientist Location: Camden, NJ - Hybrid (3 days/week onsite) only locals Duration: Long-Term ... computer vision, regression models, ensemble methods, and experimental design (A/B testing)

NT Concepts

Data Scientist

Chantilly, VA · On-site

We are seeking a Data Scientist to support disruptive Artificial Intelligence and Advanced ... You will work to enhance the efficacy of computer vision assets in scalable and secure manners to ...

Cmu

Data Scientist

Arlington, VA

Data Scientists at the SEI use advanced statistics, data analytics, machine learning, and ... Our current work includes research in generative AI and large language models, computer vision ...

Koniag, Inc.

Data Scientist

Stennis Space Center, MS · On-site

Computer vision * Natural language processing * Cloud computing platforms (AWS, Azure, GCP) * Big ... Scientific computing * Geospatial data formats and standards * Publications in peer-reviewed ...

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Computer Vision Data Scientist information

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$46K

$165K

$243.5K

How much do computer vision data scientist jobs pay per year?

As of Jun 13, 2026, the average yearly pay for computer vision data scientist in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What are Computer Vision Data Scientists?

Computer Vision Data Scientists are professionals who use data science techniques and machine learning to enable computers to interpret and understand visual information from images or videos. They design and develop algorithms that can detect, recognize, and classify objects, faces, scenes, and activities within visual data. Their work is critical in applications like autonomous vehicles, medical imaging, surveillance, and augmented reality. They often work with deep learning frameworks, large datasets, and require strong programming and analytical skills.

What are the key skills and qualifications needed to thrive as a Computer Vision Data Scientist, and why are they important?

To thrive as a Computer Vision Data Scientist, you need a strong background in machine learning, computer vision algorithms, and programming skills in languages like Python, often supported by a relevant degree in computer science or a related field. Familiarity with deep learning frameworks (such as TensorFlow or PyTorch), experience with image processing libraries (like OpenCV), and knowledge of cloud platforms are typically required. Strong analytical thinking, creativity in problem-solving, and effective communication skills help in developing innovative solutions and collaborating with cross-functional teams. These skills are crucial for building robust computer vision models that drive impactful applications in areas like autonomous vehicles, healthcare, and retail.

What is the difference between Computer Vision Data Scientist vs Computer Vision Engineer?

AspectComputer Vision Data ScientistComputer Vision Engineer
Required SkillsData analysis, statistical modeling, machine learning, programming (Python, R)Software development, algorithm implementation, system deployment
Work EnvironmentResearch, data analysis, model developmentSoftware engineering, system integration, deployment
Common CertificationsMachine Learning, Data Science certificationsComputer Vision, Software Engineering certifications
Industry UsageResearch labs, data-driven companies, academiaTech companies, startups, product development teams

While both roles involve computer vision, the Computer Vision Data Scientist focuses on analyzing data, developing models, and deriving insights, whereas the Computer Vision Engineer emphasizes building, deploying, and maintaining computer vision systems in production environments.

How does a Computer Vision Data Scientist typically collaborate with cross-functional teams in a project setting?

As a Computer Vision Data Scientist, you will frequently collaborate with software engineers, product managers, and domain experts to develop and deploy machine learning models. You may work closely with data engineers to source and preprocess large datasets, and partner with software developers to integrate your models into production systems. Effective communication is crucial, as you'll need to explain complex technical concepts to non-technical stakeholders and translate business requirements into actionable data science tasks. This collaborative environment fosters innovation and ensures that computer vision solutions are aligned with broader organizational goals.
What cities are hiring for Computer Vision Data Scientist jobs? Cities with the most Computer Vision Data Scientist job openings:
What states have the most Computer Vision Data Scientist jobs? States with the most job openings for Computer Vision Data Scientist jobs include:

Principal AI Data Scientist

MSR Technology Group

Phoenix, AZ • Remote

Full-time

Posted 1 hour 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.