Okay, I've searched for Data Scientist positions specializing in Generative AI in Atlanta, GA, full-time roles requiring a Master's degree or higher, and at least 2 years of experience in AI or Machine Learning. I have found 47 positions for you.

Sure. Here's the analysis:

Job Analysis:

The Data Scientist, GenAI role at AIG is fundamentally about pioneering the integration of generative artificial intelligence within the insurance industry to drive innovation in risk management and customer service. This position requires not just typical data science skills but a specialized focus on generative AI technologies—transformers, GPT models, few-shot learning, and Retrieval-Augmented Generation—which signals the company's ambition to disrupt and advance its core business through cutting-edge machine learning applications. Candidates must be comfortable navigating the full machine learning lifecycle, from initial data wrangling and modeling to operational deployment, reflecting a hands-on, product-oriented approach where solutions must translate into measurable business impact. The role's emphasis on working cross-functionally with product managers, engineers, and business leaders implies a collaborative environment where communication and alignment are critical to success. The preference for advanced STEM degrees and research publications underscores the complex, experimental nature of the problems being tackled, such as improving LLM efficacy and applying AI ethically within regulated environments. Candidates will face the challenge of balancing technical rigor with practical deployment amid evolving AI landscapes. Success in this role likely means delivering scalable, innovative AI-driven products that enhance AIG’s competitive edge by transforming data into personalized, efficient insurance solutions while continuously adapting to new technological developments and regulatory constraints.

Company Analysis:

AIG is a global insurance leader firmly committed to technological innovation and digital transformation, especially through initiatives like its new generative AI team. Positioned as a stable yet forward-looking organization, AIG combines the scale of a worldwide insurer with ambitions to pioneer AI applications that reshape risk management practices. This environment likely blends traditional industry rigor—especially around ethics and compliance—with the agility and creativity needed to explore AI frontiers. The company culture values in-person collaboration, signaling an emphasis on teamwork and open communication to solve complex challenges. Inclusion and diversity are clearly prioritized, suggesting a supportive workplace where varied perspectives fuel innovation. Within the organizational hierarchy, this Data Scientist role acts as a key contributor and cross-functional collaborator rather than an isolated individual contributor, with visibility across product and engineering functions and some influence on strategic AI directions. Strategically, this hire reflects AIG’s growth and innovation goals, positioning AI not just as a tool but as a central component of their evolving business model. Candidates seeking to thrive here should be excited by both cutting-edge research and practical impact, appreciate the balance between structure and innovation, and be motivated by contributing to a mission with wide-reaching implications.

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

• Behavioral: Tell me about a time when you had to collaborate with cross-functional teams to implement a complex AI or data science solution. How did you manage differing priorities and communication challenges?
• Behavioral: Describe an instance when you faced ambiguity in a machine learning project. How did you approach problem-solving and decision-making in that context?
• Behavioral: Give an example of how you stayed current with emerging AI technologies and applied that knowledge to improve a project or product.
• Behavioral: Share an experience where ethical or regulatory considerations influenced your data science approach. How did you ensure compliance while maintaining innovation?
• Technical: How would you approach developing and validating a generative AI model to improve customer personalization within an insurance product?
• Technical: Explain your experience with full ML lifecycle management, particularly deploying models into production in regulated, complex environments.
• Technical: Can you describe your familiarity with Retrieval-Augmented Generation (RAG) and prompt engineering? How have you leveraged these techniques to enhance large language model performance?
• Technical: Discuss your experience with Python and PySpark for data engineering tasks, especially in building scalable, production-ready data pipelines.
• Situational: Imagine you discover that a deployed AI model is generating biased outputs affecting certain customer groups. How would you address this issue both technically and organizationally?
• Situational: If faced with conflicting input from business leaders and engineering teams about AI product features, how would you navigate and reconcile these to move the project forward?
• Situational: Suppose you are tasked with building a framework to measure the efficacy of a newly implemented LLM. What metrics and methods would you prioritize and why?
• Company Fit: What draws you to AIG’s approach to integrating generative AI within the insurance industry?
• Company Fit: How do your personal values and career goals align with AIG’s culture of inclusion, innovation, and collaborative in-person work environment?
• Company Fit: Given AIG’s emphasis on ethical AI, how would you balance the drive for innovation with regulatory and compliance requirements in your work?
• Candidate Questions: Can you describe how the GenAI team collaborates with other departments within AIG to ensure AI solutions meet business needs?
• Candidate Questions: What are the most significant challenges the GenAI team expects to face in the next 12 months, and how can someone in this role contribute to overcoming them?
• Candidate Questions: How does AIG support continuous learning and professional development for Data Scientists working with cutting-edge AI technologies?