Okay, I've searched for AI Analyst roles in the United States that are full-time, require 3+ years of experience, and involve skills in Azure Cognitive Services and SQL. I have found 142 positions for you.

Sure. Here's the analysis:

Job Analysis:

The Analyst - AI role at Paradigm is fundamentally focused on bridging advanced AI technology with practical product applications in the residential construction and building products industry. The candidate is expected not just to be a data handler but a critical validator and integrator of AI models—particularly computer vision and large language models (LLMs)—ensuring their precision, performance, and reliability before embedding them into broader product ecosystems. This requires a blend of technical proficiency in AI tools (especially Azure AI services), rigorous data and model evaluation skills, and the ability to communicate complex AI concepts clearly to diverse stakeholders. The role demands a proactive problem-solver comfortable navigating ambiguous challenges such as edge-case detection, hallucination in LLMs, or integration inconsistencies, often needing to collaborate cross-functionally with AI scientists, developers, and product managers. Success in this role will be defined by the smooth deployment and continual improvement of AI capabilities that directly enhance product reliability and customer trust, alongside insightful reporting to guide business decisions. Strong organizational skills and adaptability are crucial given the fast-paced environment and evolving AI landscape. Prior experience with construction or architectural domain knowledge would further help tailor AI insights to industry-specific nuances, adding strategic value to the company's offerings.

Company Analysis:

Paradigm operates as a technology leader within the niche—but globally significant—residential construction and building products market. It is positioned as an innovation-driven, entrepreneurial company that values energy, learning, and skill growth, aiming for operational excellence and sales impact through its scalable platform. This market positioning means the Analyst - AI role carries significant strategic weight; this person helps translate cutting-edge AI advancements into tangible solutions for a traditional, complex industry. The culture's entrepreneurial and fast-paced nature suggests a work environment that values agility, ownership, and continuous development, where technical expertise must be paired with strong interpersonal and communication skills. Paradigm’s emphasis on teamwork and cross-functional collaboration means this role will likely have high visibility and influence spanning technical teams and product leadership. As Paradigm continues to scale and refine its product offerings with AI innovations, this position is critical in ensuring those innovations align with business goals and deliver measurable impact. The role supports Paradigm’s larger vision of digital transformation and operational efficiency improvements in a historically analog sector, making it both a growth-oriented and strategically vital hire.

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

• Behavioral: Tell me about a time when you had to validate or troubleshoot a complex AI model output. How did you approach identifying and resolving issues?
• Behavioral: Describe a situation where you had to explain a complex technical concept to a non-technical stakeholder. What strategies did you use to ensure understanding?
• Behavioral: Give an example of a project where you worked with cross-functional teams. How did you manage competing priorities and ensure collaboration?
• Behavioral: Share an experience where you adapted quickly to a sudden change in project requirements or technology. How did you maintain performance?
• Technical/Role-Specific: How would you design a validation framework to rigorously test a computer vision model before product integration?
• Technical/Role-Specific: Can you walk me through your experience with Azure AI services, especially deploying and fine-tuning models using Azure ML Studio?
• Technical/Role-Specific: What methods do you use to detect and mitigate hallucinations in large language models? How would you communicate these concerns to product teams?
• Technical/Role-Specific: Describe your process for using SQL and tools like Databricks or Power BI to analyze data quality and support AI model evaluation.
• Situational: Imagine a product team reports unexpected AI model behavior after deployment affecting user experience. How would you investigate and address this issue?
• Situational: You receive conflicting feedback from AI scientists and product managers about model performance priorities. How do you reconcile and move forward?
• Situational: Suppose you uncover data inconsistencies that impact AI outputs but the root cause is unclear. What steps would you take to identify and resolve the problem?
• Company Fit/Motivation: What interests you most about applying your AI skills within the residential construction and building products industry, especially at Paradigm?
• Company Fit/Motivation: Paradigm emphasizes an entrepreneurial and collaborative culture. How do you see yourself contributing to and thriving in this environment?
• Company Fit/Motivation: How do your professional values and career goals align with Paradigm’s mission to transform traditional industries with technology?
• Questions for Interviewer: Can you describe how the AI team collaborates with product and engineering teams on a day-to-day basis at Paradigm?
• Questions for Interviewer: What are the biggest challenges Paradigm currently faces in integrating AI solutions into its platform, and how can this role directly impact those?
• Questions for Interviewer: How does Paradigm support ongoing learning and professional growth for employees working in emerging technologies like AI and ML?