I've found several Senior Data Modeler roles in the United States within the P&C insurance industry. They all require 7+ years of experience and are contract positions with full-time hours. In total, there are 82 positions that match your criteria.

Sure. Here's the analysis:

Job Analysis:

The Senior Data Modeler role at Braintrust fundamentally seeks a candidate who can expertly design and maintain data models that cater specifically to the intricacies of Property & Casualty (P&C) insurance. This position is built around the need for thorough collaboration, as the ideal candidate will interact not only with data engineers but also with various business stakeholders like underwriting and finance teams. Key responsibilities encompass creating data structures that support operational and analytical functions—thus reflecting an understanding of how data drives business decisions in the insurance domain. Given the relationship with major enterprises, a focus on optimizing models for performance, integrity, and scalability is essential to ensure operational efficiency. Success in this role would likely manifest in timely project completions, effective stakeholder communication, and seamless integration of data that meets regulatory standards. Understanding the nuances of P&C insurance data will allow the candidate to translate complex business requirements into actionable insights effectively. The role demands significant independence and problem-solving capacity, particularly in navigating inter-departmental data requirements and ensuring alignment with industry standards.

Company Analysis:

Braintrust, as an innovator in the hiring sector with its AI-driven recruiting platform, positions itself at the intersection of technology and human resource optimization. This company is not just a service provider; it’s a transformative entity aiming to enhance talent acquisition for major corporations. The culture at Braintrust likely values agility, innovation, and cross-functional collaboration, given its emphasis on streamlining recruiting processes for top-tier clients. For the Senior Data Modeler, operating in such a fast-paced and transformative environment can present both opportunities and challenges—particularly concerning the alignment of data structures with evolving business needs. The organizational context suggests this position is critical to ensuring that robust data management supports the company's overarching strategies and operational goals. This role is likely aimed at strengthening product offerings, thus indicating an investment in data quality and governance to uphold Braintrust’s reputation as a market leader within the recruitment technology space.

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

• Describe a time when you successfully translated complex business requirements into a data model. What steps did you take?
• Can you provide an example of a challenging project where you had to collaborate with multiple stakeholders? How did you manage differing priorities?
• Tell me about a specific instance where your data modeling decisions had a significant impact on business operations.
• How do you approach optimizing data models for performance and scalability? Can you give an example?
• What experience do you have with industry standards, such as ACORD, in developing data models?
• Describe your proficiency with SQL and how you have utilized it in your previous roles related to data modeling.
• How would you handle a situation where a critical data integration project is falling behind schedule?
• Imagine you are given a set of disparate data sources with inconsistent structures. How would you go about creating a unified data model?
• What strategies would you employ to ensure data quality and governance in your modeling practices?
• Why are you interested in the Senior Data Modeler position at Braintrust specifically?
• How do you see the role of data modeling evolving in the context of AI-driven solutions in recruitment?
• What questions do you have about the collaboration process with stakeholders at Braintrust?
• Can you discuss how you approach mentoring junior data modelers or analysts? What do you believe is essential for their development?