Job Description Summary

Women's Health and X-ray is pursuing a strategic initiative to unlock incremental revenue through the development of Digital SaaS solutions. These innovative applications will be layered onto the existing global install base of Mammography (Mammo), Digital Breast Tomosynthesis (DBT), and X-ray devices—transforming hardware into intelligent platforms that deliver enhanced clinical and operational value.

The Sr Data Scientist will work in teams addressing statistical, machine learning and data understanding problems in a commercial technology and consultancy development environment. In this role, you will contribute to the development and deployment of modern machine learning, operational research, semantic analysis, and statistical methods for finding structure in large data sets. The project centers on the development of solutions that leverage AI-driven guidance to assist patients throughout radiologic procedures. The system integrates advanced technologies including computer vision, robotics, and intelligent control to coordinate imaging tasks.

Job Description

** No OPT or Sponsorship for this role **

** This role is a hybrid position, in-office 2-3 days/week **

As a Sr Data Scientist, you will be part of a data science or cross-disciplinary team on commercially facing development projects, typically involving large, complex data sets. These teams typically include statisticians, computer scientists, software developers, engineers, product managers, and end users, working in concert with partners in GE business units. Potential application areas include remote monitoring and diagnostics across infrastructure and industrial sectors, financial portfolio risk assessment, and operations optimization.

In this role, you will:

• Work with customers to capture data and analytics requirements
• Develop, verify, and validate analytics to address customer needs and opportunities.
• Work alongside software developers and software engineers to translate algorithms into commercially viable products and services.
• Work in technical teams in development, deployment, and application of applied analytics, predictive analytics, and prescriptive analytics.
• Perform exploratory and targeted data analyses using descriptive statistics and other methods.
• Work with data engineers on data quality assessment, data cleansing and data analytics
• Generate reports, annotated code, and other projects artifacts to document, archive, and communicate your work and outcomes.
• Communicate methods, findings, and hypotheses with stakeholders.

Requirements:

Education-

• Master’s or PhD in Computer Science or “STEM” Majors (Science, Technology, Engineering and Math).

• Undergraduate or graduate studies in biomedical engineering or similar fields is highly desired.

• Minimum of 7 years of professional experience in AI product development.

• Experience in medical device development

Technical Expertise-

• Demonstrated skill in data management methods

• Demonstrated skill in feature extraction and realtime analytics development and deployment

• Demonstrated skill in prescriptive analytics and analytic prototyping

• Experience developing and deploying production-grade AI/machine learning models at scale, delivering measurable business impact through improved efficiency, revenue growth or automation in real-world environments.

• Demonstrated ability to translate business problems into ROI-driven AI solutions, including end‑to‑end ownership from problem framing and model development to operationalization, monitoring, and continuous improvement in production

Specific Skills Include-

• Proficiency in python and deep learning frameworks such such a Tensorflow, PyTorch and openCV 

• Strong background in AI image processing and computer vision algorithms, including training and fine-tuning image classification and segmentation models

Preferred Skills:

• Experience with model optimization for latency and throughput in online systems.

• Experience with large-scale CNNs or LLMs, vision transformers (VLMs), and self-supervised learning.

• Experience with the full AI lifecycle, including data curation, model development, and model validation for production. Proven ability to collaborate with ML engineers to integrate models into production. Skilled in model validation for product readiness, with a strong focus on writing production-quality, maintainable code.

• Experience with multimodal data integration and systems com