Okay, I've searched for senior Evidence Lead roles in Indianapolis, IN, focused on AI models within regulated digital health solutions, requiring expertise in medical AI algorithms, and for full-time positions. I have found 23 positions matching your criteria.

Sure. Here's the analysis:

Job Analysis:

The Evidence Lead (AI models) at Roche is a senior clinical and scientific role focused on driving robust evidence generation to support the development, regulatory approval, and clinical adoption of AI-powered digital health solutions, particularly Software as Medical Devices (SaMD). The core purpose is to ensure that AI algorithms, including imaging AI models and digital biomarkers, meet stringent regulatory standards (FDA, EMA) through scientifically sound validation. Beyond regulatory interactions, this role is integral to shaping best practices in clinical validation, mentoring other evidence professionals, and advancing Roche’s leadership in digital health innovation. Candidates must navigate complex clinical research environments, balancing agility with rigor, and cross-functional collaboration with external regulatory and academic partners. Success means delivering credible, timely clinical evidence that underpins product approval and adoption while pushing boundaries through thought leadership and innovation in evidence generation methodologies. The role requires a blend of deep clinical/scientific expertise, strategic leadership, regulatory savvy, and strong project management. Given the rapidly evolving AI healthcare space, this position demands comfort with ambiguity, an “AI first” mindset, and a proactive, mentorship-driven approach to build Roche’s center of excellence for digital health evidence.

Company Analysis:

Roche occupies a commanding position as a global biotech and diagnostics leader focused on personalized healthcare, blending pharmaceuticals and diagnostics to transform how diseases are prevented, diagnosed, and treated. Its strong emphasis on innovation, sustainability, and patient-centricity sets a mission-driven and forward-thinking culture, valuing diversity, openness, and long-term impact. This progressive environment likely fosters collaboration, creative problem-solving, and agility—key for a role embedded in cutting-edge digital health technologies. As part of Roche Information Solutions, the Evidence Lead will operate within a specialized but highly visible function that interacts broadly—with internal clinical experts, regulatory bodies, and external researchers—demanding strong communication and cross-functional influence. The company’s stature and focus on regulatory excellence mean the role will have significant strategic importance in advancing AI-powered health products toward market success, aligning with Roche’s vision for a healthier future through innovation. Candidates should prepare for a culture valuing scientific rigor, ethical standards, and a mission-oriented drive while embracing technological transformation in healthcare delivery.

Absolutely. Here are some mock interview questions that could come up:

• Behavioral: Tell me about a time when you led a clinical evidence generation project that faced regulatory challenges. How did you navigate those obstacles?
• Behavioral: Describe how you have mentored or developed junior team members in a complex, specialized scientific environment.
• Behavioral: Give an example of when you had to coordinate across multiple teams or external partners to deliver a high-stakes clinical validation study.
• Behavioral: How do you handle ambiguity when working in a fast-paced, innovative environment, especially with emerging AI technologies?
• Technical: How would you design a clinical validation study to support FDA approval of a new imaging AI algorithm classified as SaMD?
• Technical: What are key considerations and challenges in generating clinical evidence for digital biomarkers used in clinical decision support systems?
• Technical: Describe your experience with regulatory submissions for AI algorithms and the critical elements needed to ensure approval.
• Technical: Can you explain the role of Good Study Practices (GSPs) and Standard Operating Procedures (SOPs) in evidence generation for AI health products?
• Situational: Imagine you discover that a pivotal clinical validation study’s data is inconclusive just prior to submission. How would you address this issue?
• Situational: If a regulatory authority requests additional evidence for a digital health product post-market, how would you coordinate and respond effectively?
• Situational: How would you foster a culture of innovation and knowledge sharing among evidence leads to accelerate best practices within your team?
• Company Fit/Motivation: What attracted you to Roche’s approach to combining diagnostics and pharmaceuticals in advancing personalized healthcare?
• Company Fit/Motivation: How do you see your expertise in AI and clinical evidence generation aligning with Roche’s mission and culture?
• Company Fit/Motivation: Roche values open dialogue and genuine connections—how do you embody these values in your professional interactions?
• Questions for Interviewer: How does Roche envision the evolution of its digital health center of excellence in the next 3–5 years?
• Questions for Interviewer: What are the biggest challenges your team currently faces in clinical validation of AI models, and how can this role make an impact?
• Questions for Interviewer: How does Roche support ongoing professional development and thought leadership for senior scientific roles like this one?