This is a fully remote position, open to applicants in United States, +1 more country.

📋 Description

• Assist the Sales, Customer Success, and Marketing teams by offering clinical expertise, conducting customer presentations, and showcasing Transpara demonstrations.

• Offer clinical and training support for research initiatives in the USA and Canada, which include the PRISM trial, various evaluations, and research projects.

• Facilitate clinical adoption and enhance customer engagement.

• Oversee and monitor the Net Promoter Score (NPS) program across the USA and Canada.

• Create and implement clinical training programs for customers, partners, and internal teams.

• Spearhead Transpara onboarding and certification training programs for both employees and partners.

• Assemble and organize clinical cases and materials for training, marketing, and conference purposes.

• Coordinate Transpara workshops, both in-person and virtual.

• Work in conjunction with Marketing and Sales to produce webinars and educational content.

• Convey customer insights to the Engineering, Innovation, and Product Management teams.

• Address and assist with clinical customer feedback and complaints.

⛳️ Requirements

• A Bachelor’s degree in a medical or relevant field.

• Clinical and technical experience related to medical imaging or AI software.

• Experience with mammography technology and/or breast imaging AI.

• Excellent presentation, communication (both verbal and written), and interpersonal skills.

• Demonstrated experience in training and educational programs.

• Willingness to travel approximately 20% of the time.

• Submission of a Certificate of Conduct (VOG) or background check is required as part of the application process.

• Experience with script programming is preferred.

🏝️ Benefits

• Flexible remote work arrangement.

• Opportunity to influence the strength of clinical claims.

• Career advancement opportunities.

• Chance to collaborate with various departments and professionals in the fields of breast imaging, machine learning, algorithm development, and clinical research.