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Imaging Data Scientist Jobs in Florida (NOW HIRING)

... imaging reports), using techniques such as tokenization, lemmatization, and word embeddings (e.g ... Data Science, AI, Computer Science, or a related field) + 10 years experience; or PhD + 4 years ...

Foundational knowledge in biology, biological science, biomedical engineering, or anatomy. * Ability to work with CT scan data and understand basic medical imaging concepts. * Proficiency in ...

Bench chemistry, microbiology, molecular biology or other scientific techniques. * Collection of preclinical and clinical imaging data * Perform other duties as assigned. Hourly Range : $ 19.80- $ 25 ...

Data Engineer

Miami, FL ยท On-site

$120K - $180K/yr

Despite the critical role of radiology in healthcare, the process for undergoing a medical imaging ... Work cross-functionally with data scientists, product managers, and other engineering teams to ...

Data Engineer

Miami, FL ยท On-site

$120K - $180K/yr

Integrate data from various structured and unstructured sources, including medical imaging systems ... Work cross-functionally with data scientists, product managers, and other engineering teams to ...

... all experimental data for managing staff. 7. Requests or acquires equipment and supplies for ... Use electrophysiology together with imaging techniques, genetically encoded sensors, and ...

... all experimental data for managing staff. 7. Requests or acquires equipment and supplies for ... Use electrophysiology together with imaging techniques, genetically encoded sensors, and ...

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Imaging Data Scientist information

What is an imaging data scientist?

An Imaging Data Scientist is a professional who specializes in analyzing and interpreting data from various imaging sources, such as medical scans, satellite images, or industrial photographs. They use advanced data analysis, machine learning, and image processing techniques to extract meaningful insights from complex image data. These scientists often collaborate with experts in fields like healthcare, remote sensing, or manufacturing to support decision-making and innovation. Their work can involve tasks such as developing algorithms for image classification, segmentation, or enhancement. The role requires strong skills in programming, statistics, and domain-specific knowledge.

How does an imaging data scientist typically collaborate with other teams in a research or clinical setting?

Imaging Data Scientists frequently work alongside radiologists, clinicians, and software engineers to develop and refine algorithms for analyzing medical images. Collaboration often involves regular meetings to interpret imaging data needs, share findings, and troubleshoot issues related to data quality or algorithm performance. They may also work closely with data engineers to ensure efficient data storage and retrieval, and with project managers to align on timelines and deliverables. This cross-disciplinary teamwork ensures that imaging solutions are both scientifically robust and practically applicable in clinical workflows.

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

To thrive as an Imaging Data Scientist, you need a strong background in computer science, mathematics, and image analysis, often supported by an advanced degree in a related field. Familiarity with programming languages like Python or MATLAB, machine learning frameworks, and image processing tools such as OpenCV or ITK is typically required. Strong analytical thinking, attention to detail, and effective communication skills help distinguish top performers in this role. These skills and qualities are crucial for developing accurate image-based models, collaborating with interdisciplinary teams, and translating complex data into actionable insights.

What is the difference between Imaging Data Scientist vs Medical Data Scientist?

AspectImaging Data ScientistMedical Data Scientist
CredentialsTypically requires a degree in data science, computer science, or related fields; familiarity with imaging softwareRequires a degree in data science, biostatistics, or healthcare-related fields; often with knowledge of medical terminologies
Work EnvironmentWorks in healthcare, research institutions, or tech companies focusing on imaging dataWorks in hospitals, healthcare organizations, or biotech firms analyzing medical data
Industry UsageUsed in medical imaging analysis, radiology, and diagnostic researchApplied in clinical research, patient data analysis, and healthcare decision support

Imaging Data Scientists focus on analyzing medical images like MRI, CT scans, and X-rays, utilizing machine learning and image processing techniques. Medical Data Scientists work with broader healthcare data, including electronic health records and clinical data. While both roles require data science skills, Imaging Data Scientists specialize in imaging modalities, making their roles distinct yet overlapping in healthcare analytics.

What job categories do people searching Imaging Data Scientist jobs in Florida look for?

The top searched job categories for Imaging Data Scientist jobs in Florida are:

What cities in Florida are hiring for Imaging Data Scientist jobs?

Cities in Florida with the most Imaging Data Scientist job openings:

Infographic showing various Imaging Data Scientist job openings in Florida as of August 2026, with employment types broken down into 91% Full Time, and 9% Nights. Highlights an 91% In-person, and 9% Hybrid job distribution.

SA - Data Scientist

RIT Solutions, Inc.

Tampa, FL โ€ข On-site

Full-time

Re-posted 15 days ago


Job description

Job Summary:
RIT Solutions, Inc. is seeking a skilled Data Scientist with deep expertise in developing AI models, particularly in natural language processing (NLP). The role focuses on analyzing unstructured medical records, developing AI models for extracting insights, and integrating feedback to improve model performance.
Responsibilities:
โ€ข Develop and fine-tune AI models for natural language processing (NLP) tasks, including Named Entity Recognition (NER), text classification, and sentiment analysis, particularly with unstructured clinical records
โ€ข Conduct experiments to evaluate model performance, utilizing metrics such as precision, recall, and F1-score to iteratively improve models through hyperparameter tuning and training optimizations
โ€ข Analyze and preprocess large datasets, particularly unstructured medical records (e.g., physician notes, discharge summaries), using tools like Pandas, NLTK, and SpaCy
โ€ข Create custom NLP algorithms and annotators to evaluate medical record data
โ€ข Create custom tools to enable analysts to perform data research
โ€ข Identify and analyze user requirements to generate stories and tasks for team backlog
โ€ข Prioritize and execute tasks throughout the software development life cycle
โ€ข Demonstrated experience analyzing and processing unstructured clinical data (e.g., electronic health records, physician notes, imaging reports), using techniques such as tokenization, lemmatization, and word embeddings (e.g., TF-IDF, BERT)
โ€ข Familiarity with healthcare data formats and standards such as HL7, FHIR, ICD codes, and SNOMED
โ€ข Experience with cloud platforms (AWS, Azure), containerization (Docker), and using CI/CD pipelines for machine learning model deployment
โ€ข Knowledge of SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Elasticsearch) databases, and how to structure data pipelines for efficient data processing
โ€ข Ability to effectively articulate technical challenges and solutions
โ€ข Strong communicator with excellent written and verbal communication skills
โ€ข Knowledge about Agile development Methodologies
Qualifications:
Required:
โ€ข 5+ years of experience in AI/Client development with a strong focus on NLP using frameworks such as TensorFlow, PyTorch, and Hugging Face
โ€ข Expertise in Python, with experience in libraries like Transformers, NLTK, SpaCy, Gensim, and data manipulation tools such as Pandas and NumPy
โ€ข Experience working with human-in-the-loop systems, integrating clinician feedback to refine AI models
โ€ข Ability to effectively articulate technical challenges and solutions
โ€ข Strong communicator with excellent written and verbal communication skills
โ€ข Knowledge about Agile development Methodologies
โ€ข Identify and analyze user requirements to generate stories and tasks for team backlog
โ€ข Prioritize and execute tasks throughout the software development life cycle
โ€ข Create custom NLP algorithms and annotators to evaluate medical record data
โ€ข Create custom tools to enable analysts to perform data research
โ€ข Solid understanding of statistical modeling, data analysis, and performance evaluation metrics
โ€ข Demonstrated experience analyzing and processing unstructured clinical data (e.g., electronic health records, physician notes, imaging reports), using techniques such as tokenization, lemmatization, and word embeddings (e.g., TF-IDF, BERT)
โ€ข Familiarity with healthcare data formats and standards such as HL7, FHIR, ICD codes, and SNOMED
โ€ข Experience with cloud platforms (AWS, Azure), containerization (Docker), and using CI/CD pipelines for machine learning model deployment
โ€ข Knowledge of SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Elasticsearch) databases, and how to structure data pipelines for efficient data processing
โ€ข Develop and fine-tune AI models for natural language processing (NLP) tasks, including Named Entity Recognition (NER), text classification, and sentiment analysis, particularly with unstructured clinical records
โ€ข Conduct experiments to evaluate model performance, utilizing metrics such as precision, recall, and F1-score to iteratively improve models through hyperparameter tuning and training optimizations
โ€ข Analyze and preprocess large datasets, particularly unstructured medical records (e.g., physician notes, discharge summaries), using tools like Pandas, NLTK, and SpaCy
โ€ข Master's degree (Data Science, AI, Computer Science, or a related field) + 10 years experience; or PhD + 4 years
Preferred:
โ€ข Experience in healthcare, particularly working with unstructured medical records in clinical settings, leveraging NLP models for insight extraction
โ€ข Experience working with human-in-the-loop systems, incorporating clinician/end-user feedback and leveraging tools like SciPy and NumPy to improve AI model accuracy
โ€ข Educational background or practical training in a clinical setting, with exposure to clinical workflows and medical terminologies
โ€ข Familiarity with deep learning techniques, attention mechanisms, and transformers applied to healthcare data
Company:
Jobdiva Job Portal: https://www1.jobdiva.com/candidates/myjobs/searchjobsdone.jsp?a=xbjdnwgjodtga1y1im2g881fkkeiwd0775lbvq8yqgps8vb2q36w2vj1ga6xxork&compid=-1 Recruitment (contingency search and campus selection). Founded in 2019, the company is headquartered in Arlington, USA, with a team of 201-500 employees. The company is currently Growth Stage.