Okay, I've searched for Principal Data Scientist roles in Houston, TX within the healthcare industry, requiring 10+ years of experience, proficiency in Python and R, for remote full-time positions. I have found 27 suitable openings for you.

Sure. Here's the analysis:

Job Analysis:

This Principal Data Scientist role at Molina Healthcare is a high-impact leadership position designed to spearhead the organization's advanced data science initiatives, particularly around generative AI and machine learning in healthcare. Fundamentally, the hire will be expected to bridge the gap between cutting-edge AI research and practical, scalable healthcare solutions that enhance operational efficiency and member experience. This entails not only deep technical expertise—including proficiency in Python, R, machine learning frameworks (TensorFlow, PyTorch), and advanced AI techniques like agentic workflows and retrieval-augmented generation (RAG)—but also a strategic mindset to align data science projects with evolving business objectives and regulatory environments. The candidate must navigate complex healthcare data while ensuring ethical and governance compliance, indicating a high degree of accountability and judgment. They will confront challenges such as model deployment and governance, cross-functional collaboration with software engineers and product teams, and translating technical insights into actionable business intelligence. Success in this role will be measured by the ability to deliver innovative AI-driven solutions that improve key healthcare metrics, maintain model reliability in production, and effectively mentor and lead a growing data science team. With 10+ years of experience required, the role demands seasoned problem-solving, holistic project ownership, and the agility to adapt advanced AI tools to real-world healthcare scenarios while continuously staying ahead of technical and industry advancements.

Company Analysis:

Molina Healthcare is a prominent player in the healthcare sector, blending stability with an ambition to innovate through data-driven decisions and technology. The collaboration with Lensa for talent acquisition reflects Molina’s commitment to leveraging AI and machine learning not only internally but also in shaping how talent meets opportunity. Molina's positioning as a healthcare provider that seeks to improve member outcomes and operational efficiencies places a premium on roles that can pioneer AI solutions within regulatory frameworks. The culture implied is mission-driven yet technologically progressive, balancing regulatory compliance and innovation—ideal for someone who thrives in structured environments but is eager to push technological frontiers. The environment likely values transparency, cross-team coordination, and the translation of complex data insights into practical business strategies, creating a space where technical leadership is highly visible and influential. Given the remote and Houston-based location with ties to a growing AI workforce, this role sits at the intersection of healthcare delivery and technology innovation, reporting into senior leadership or a chief data office, and expected to act as a strategic pioneer for AI in healthcare. The strategic hire aligns closely with scaling and modernizing Molina's AI capabilities, supporting enterprise-wide goals such as improving quality metrics, care delivery, and payment integrity, while fostering a culture of continuous learning and mentorship within the data science function.

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

• Behavioral: Tell me about a time when you had to lead a data science project involving cross-functional teams. How did you ensure alignment and successful delivery?
• Behavioral: Describe an instance where you had to mentor a junior data scientist. What approach did you take and what was the outcome?
• Behavioral: Explain a situation where you identified a gap in AI model performance post-deployment. How did you address it?
• Behavioral: Can you share an experience where you had to communicate complex technical concepts to a non-technical stakeholder? How did you ensure understanding?
• Technical: What strategies do you use to deploy and monitor machine learning models in production, particularly in a regulated environment such as healthcare?
• Technical: How would you design and implement agentic workflows to automate operational tasks? Can you provide an example from your past work?
• Technical: Walk me through your experience with retrieval-augmented generation (RAG) techniques and how you have applied them to improve AI model outputs.
• Technical: Describe your approach to fine-tuning pre-trained models for specific healthcare applications. What factors do you consider critical?
• Situational: Imagine a newly deployed AI model starts producing biased outcomes that could impact patient care negatively. How would you identify, address, and prevent this?
• Situational: You have to convince the leadership team to invest in cutting-edge generative AI projects with uncertain outcomes. How would you build your case?
• Situational: A cross-functional team is resisting the integration of AI-enhanced workflows citing complexity and lack of understanding. How would you facilitate adoption?
• Company Fit: Why are you interested in applying your data science expertise specifically within Molina Healthcare’s environment?
• Company Fit: How do you see your experience with generative AI and machine learning advancing Molina’s mission to improve member experience and healthcare operations?
• Company Fit: Molina emphasizes ethical data use and regulatory compliance. How do your values and working style align with these priorities?
• Candidate to Ask: How does Molina balance innovation with compliance when deploying AI solutions in healthcare?
• Candidate to Ask: Can you describe the team structure and leadership support for data science initiatives, especially for generative AI projects?
• Candidate to Ask: What are the biggest challenges Molina anticipates in scaling AI-driven healthcare solutions over the next 1-2 years?