Associate Data Scientist Algorithm Research TMI

The primary purpose of the Associate Data Scientist position is to assist researching and assisting researchers in creating high impact imaging and pathology machine learning algorithms for the Tumor Measurements Initiative (TMI) . In this role, the candidates will focus on the following areas:

• Developing state-of-the-art computer vision tools to derive precise tumor measurements from medical imaging, pathology, and other data sources.
• Collaborate closely with our team of research data scientists to create deep learning methodologies and impactful AI algorithms.
• Maintain diligent records of model development experiments, data and model lineage tracking, and create comprehensive model scorecards.
• Responsible for conducting a thorough evaluation of model performance, as well as analyzing bias and equity to ensure our commitment to responsible AI.
• Collaboration with ML Engineers to enable rapid experimentation and impact by creating data and ML pipelines, rapid deployments, and model monitoring.

Technical Expertise
Develop and deploy impactful computer vision models for segmenting and interpreting complex medical imaging data.
Proficiency in Python, complemented by experience with machine learning libraries such as TensorFlow, PyTorch, and Scikit-learn.
Work with state-of-the art machine learning algorithms and training methods for computer vision.
Working knowledge of transformers and generative AI
Using code and model management tools to track experiments and ensure reproducibility (e.g. Git, HuggingFace, MLFlow)
Experience with essential software engineering principles.
Working on-premise, cloud-based, and hybrid computing environments.

Analytical Skills
Maintaining features, assist with data labeling, ML artifact management, and analytics to ensure high data quality, versioning, and performance tracking.
Perform testing, debugging, and code quality checks.
Working with medical imaging data and understanding medical imaging workflows.
Familiarity with healthcare data standards and ontologies, such as DICOM, HL7, FHIR.
Familiarity with healthcare data privacy, such as HIPAA and/or GDPR.

Professionalism: Oral and Written
Assist researchers to gather initial requirements, analyze clinical data, design and develop ML solutions, perform feasibility testing of proposed solutions, evaluate and interpret the results.
Concisely and clearly present technical and non-technical and progress updates in project meetings as well as external meetings, workshops, conferences, etc.
Communicate effectively and cooperatively with leaders, peers, end users and support teams when required.

Other duties as assigned

Education Required: Bachelor's degree in Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Statistics, Computer Science, Computational Biology, or related field.

Preferred Education: Master's Level Degree

Experience Required: Two years' experience in scientific software development/analysis.

Preferred Experience: Experience with Azure, and proficiency in cloud-native tools and services such as Azure Arc, Azure ML and Azure Cognitive Compute (or similar).

Onsite Presence: Is Required

It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state or local laws unless such distinction is required by law. http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html