The Verification & Validation Engineer will be deeply involved in product testing, simulated use, and cross-functional collaboration with design, manufacturing, QA, product marketing, and product management teams. This is a hands-on, customer-facing role requiring direct engagement with surgeons and surgical teams to design and execute verification and validation activities. Core Responsibilities Lead verification and validation (V&V) activities for new product development and sustaining engineering.Write test plans, protocols, and reports; execute testing in labs; oversee vendor testing.Plan and lead simulated use testing with surgeons and surgical teams (logistics, execution, reporting).Support regulatory and design control requirements.Collaborate cross-functionally with design engineers, manufacturing, QA/RA, and product management.Author verification and validation documentation to support regulatory submissions.Support risk analysis activities. Requirements Strong verification and validation experience in medical devices (not software).Proven experience writing protocols and reports from scratch.Excellent technical writing and communication skills (clear, concise, explaining the “why”).Hands-on experience with simulated use testing; ability to lead protocols and coordinate with surgeons.Proactive and confident personality. Ability to take initiative, ask questions, and lead discussions.  Nice-to-Haves Orthopedics experience.Mechanical testing background (e.g., MTS, materials testing).Fixture design capability (machining/3D printing); team has support if candidate can’t build solo.Root cause/sustaining engineering experience.Awareness of materials testing or design experience (as long as candidate is committed to V&V focus).  Ideal Profile Engineering degree (Mechanical, Biomedical, or related).Minimum 3–5 years in medical device V&V (with flexibility if candidate has advanced degree + practical experience).Comfortable in a fast-paced environment.Confident communicator who can work directly with clinicians and cross-functional teams.Strong organizational skills and ability to balance writing/documentation with hands-on testing (approx. 50/50 or 60/40 split). Additional Notes Relocation: No formal package

SciPro has partnered with a high-growth cloud-based healthtech company at the forefront of digital transformation in life sciences, seeking a Data Architect. With deep integration across the world’s leading cloud and AI platforms, this company is redefining how scientific organizations collect, structure, and activate their R&D data to power next-generation discovery. They are looking for a Data Architect to collaborate directly with scientific stakeholders and internal cross-functional teams to deliver complex, data-centric solutions across the biopharma ecosystem. This role is key to translating lab-based workflows into scalable digital solutions, driving implementation of scientific data pipelines, and accelerating customers’ ability to leverage AI-ready data. This role is located in Boston, New York City, or San Fransisco. Responsibilities Translate lab workflows and scientific use cases into data-driven solutions using the company’s proprietary platformDevelop and implement technical components including Python-based data parsing, structured data design (JSON schemas), and lab software integration via APIsCreate interactive visualizations using Python (Jupyter, Streamlit, hvPlot, etc.) or commercial BI tools (PowerBI, Tableau, Spotfire)Conduct detailed interviews with customer teams to gather business and scientific requirementsWork cross-functionally with customer stakeholders and internal teams to ensure delivery of fit-for-purpose solutionsLead account sprint planning, manage delivery milestones, and communicate progress through customer demos and updatesIdentify reusable solution components to inform future product developmentServe as a technical and scientific thought partner to customers, enabling long-term platform adoption and impact  Main Qualifications 7+ years (PhD) or 10+ years (Masters) of hands-on experience using Python for data analysis, automation, or scientific data engineering3+ years of experience in the life sciences domain (biotech, pharma, bioinformatics, or scientific software vendor)Strong Data Modelling skills (SQL, noSQL, Ontologies)Strong ability to translate complex scientific needs into technical specifications and data architecturesExperience integrating ELNs, LIMS, or other lab systems via APIsExcellent communication, critical thinking, and problem-solving skills with a collaborative mindsetStrong customer orientation and the ability to manage delivery independently in a fast-paced environmentFamiliarity with cloud technologies (AWS, Azure, GCP) is a plus