Clinical Product Manager - EU or USA

March 15

🍂 Massachusetts – Remote

Although this job is listed in Massachusetts, this company may be open to hiring remote in other states.

💵 $100k - $130k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

✅ Product Manager

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DeepHealth

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DeepHealth is a global leader in AI-powered health informatics, providing innovative solutions designed to enhance operational efficiency and clinical confidence in radiology. As a wholly-owned subsidiary of RadNet, Inc. , DeepHealth offers a comprehensive suite of diagnostic and imaging tools, including the DeepHealth OS, a pioneering cloud-native operating system. Their AI-powered solutions support large-scale diagnostic programs and streamline workflows in areas such as breast, prostate, lung, and brain cancer detection. DeepHealth collaborates with leading healthcare institutions worldwide to transform radiology practices and improve care delivery.

11 - 50 employees

🤖 Artificial Intelligence

⚕️ Healthcare Insurance

☁️ SaaS

💰 $225k Grant on 2019-08

📋 Description

• As a Clinical Product Manager you will play a critical role in managing network of innovation partner sites for testing and validating new solutions while generating clinical and operational evidence to support the company’s offerings. • The Clinical Product Manager is accountable to designing, executing, and analyzing clinical studies that support the development and validation of innovative healthcare technologies. • Collaborate with cross-functional teams, including R&D, regulatory affairs, and medical affairs, to ensure scientific rigor and compliance with global regulatory standards. • Developing, delivering, and disseminating strategies to support clinical evidence. • Collaborating with internal teams and external partners to initiate and support research programs. • Providing feedback and input on the roadmap towards long-term clinical strategies. • Promoting branding and innovations, developing, managing, and steering partnerships. • Management and execution of clinical studies including creating project plans and documentation such as study protocols, data management plan, analysis plan, project deliverables, timelines, and stakeholder management. • Ensure adherence to Good Clinical Practice (GCP), ethical standards, and applicable regulations. • Provide clinical expertise in interactions with regulatory authorities and external partners. • Develop scientific presentations, publications, to support Marketing Activities. • Analyze and interpret clinical data to evaluate the safety, efficacy, and performance of products. • Collaborate with cross-functional teams, including data scientists, engineers, clinicians, and researchers to integrate clinical insights into product design and refinement. • Work with healthcare professionals to gather feedback, identify unmet needs, and validate clinical use cases in Beta phase. • Establish and maintain strong relationships with clinical partners, including hospitals, research institutions, and healthcare providers. • Serve as the primary point of contact for clinical collaborators, facilitating effective communication and coordination. • Work on-site with clinical collaborators to support the evaluation, implementation, troubleshooting, and optimization of (research) products in real-world environments. • Develop KOL relationship and Advisory community.

🎯 Requirements

• Advanced degree (Ph.D., MD, PharmD, or equivalent) in a relevant scientific or medical field. • Strong background in clinical research, preferably in medical devices, diagnostics, or digital health. • Experience designing and managing clinical studies. • Proficient in statistical analysis and clinical data interpretation. • Knowledge of regulatory standards (e.g., FDA, ISO 14155, ICH-GCP) • Excellent written and verbal communication skills. • Clinical experience or expertise in a specific therapeutic area (e.g., radiology, oncology, cardiology). • Strong project management skills with the ability to work in a fast-paced, dynamic environment. • Proven experience with clinical data statistics and ability to apply this to clinical study design. • Experience evaluating machine learning models.