Okay, I've searched for Lead Data Scientist roles in Detroit, MI within the healthcare industry, requiring 5+ years of experience, skills in machine learning and Python, for full-time positions. I have found 23 positions for you.

Sure. Here's the analysis:

Job Analysis:

The Lead Data Scientist role at Henry Ford Health is fundamentally centered on architecting and delivering advanced data science solutions that address complex healthcare business challenges. This role demands a strategic thinker who can translate loosely defined problems into scalable, effective analytics projects, encompassing predictive modeling, machine learning, and natural language processing. Given the healthcare setting, the candidate must grapple with multifaceted data sources—both structured and unstructured—while ensuring compliance with regulatory standards and driving actionable insights that improve patient outcomes and operational efficiency. Leadership and collaboration are critical, as the lead scientist not only guides junior team members but also must effectively communicate technical findings to diverse stakeholders, including system leaders and business analysts. Mastery of cloud environments (specifically Azure), agile methodologies, and a robust tech stack (Python, R, SQL, Power BI) enables deployment and monitoring of models in production, emphasizing continuous learning and adaptability. Success looks like the ability to manage multiple projects, prioritize based on business impact, and foster adoption of data-driven decisions across the organization.

Company Analysis:

Henry Ford Health is a prominent, mission-driven academic medical center and healthcare system deeply embedded in Michigan with a broad continuum of services from primary care to specialty treatments. As a leading NIH-funded institution and a substantial employer, it balances research, education, and exemplary patient care within a large and diverse operational ecosystem. The company culture likely values innovation, multidisciplinary collaboration, and a commitment to improving community health outcomes—a natural fit for a role demanding both technical expertise and cross-functional communication. The Lead Data Scientist position fits into a growing data-driven strategy to leverage enterprise data warehouse capabilities at scale, driving insights for system-wide improvements. This implies strong visibility and impact potential but also the challenge of navigating complex healthcare workflows, stakeholder needs, and regulatory frameworks. Given the organization's scale and focus on cutting-edge care, this role offers both the opportunity to influence large initiatives and the need to adapt rapidly within a dynamic environment.

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

• Behavioral: Tell me about a time when you had to design a data science solution for a complex healthcare problem with ambiguous requirements. How did you approach it?
• Behavioral: Describe a situation where you led a team through multiple competing projects. How did you prioritize and ensure timely delivery?
• Behavioral: Can you share an experience where you had to communicate technical findings to a non-technical audience? What strategies did you use to ensure understanding and buy-in?
• Behavioral: Give an example of how you handled a conflict or disagreement within a cross-functional project team.
• Technical: How would you architect an expandable machine learning solution that utilizes both structured and unstructured healthcare data in a cloud environment like Azure?
• Technical: What techniques and tools do you rely on for automating model deployment, monitoring, and retraining in production healthcare analytics systems?
• Technical: Walk me through how you would use predictive modeling to solve a forecasting problem related to patient readmissions or clinical outcomes.
• Technical: What experience do you have with NLP or large language models in healthcare analytics, and how would you incorporate these technologies responsibly?
• Situational: Imagine you discover that a deployed machine learning model’s performance is degrading over time. How would you identify root causes and address the issue?
• Situational: Suppose a business stakeholder requests a quick solution to a new problem but data is incomplete or inconsistent. How would you manage expectations and proceed?
• Situational: You are assigned to lead a project with a geographically distributed team with varying levels of data science expertise. How would you ensure effective collaboration and delivery?
• Company Fit: Why are you interested in working at Henry Ford Health and how do you see your values aligning with its mission to serve community health and innovation?
• Company Fit: Given Henry Ford Health’s emphasis on education, research, and clinical excellence, how do you think the Lead Data Scientist role can contribute to these areas?
• Company Fit: Henry Ford Health operates across many sites with diverse teams. How would you adjust your leadership and communication style to be effective in this environment?
• Candidate Questions: What are the current biggest data science challenges Henry Ford Health is looking to solve with the Enterprise Data Warehouse team?
• Candidate Questions: How does the data science team collaborate with clinical and operational stakeholders to ensure analytics projects drive measurable improvements?
• Candidate Questions: Can you describe the Agile practices currently in place and how the Lead Data Scientist role interfaces with other teams and leadership?