Okay, I've searched for Data Scientist roles in North Carolina, full-time, requiring 3 years+ experience, with skills in Python and SQL, and a yearly paid salary range of $100,000 to$199,000. I have found 126 positions for you.

Sure. Here's the analysis:

Job Analysis:

This Data Scientist role within Microsoft Advertising is fundamentally about using data-driven methods to optimize a large, complex marketplace that connects advertisers and publishers worldwide. The candidate is expected to build and refine metrics that accurately measure product and marketplace success, design thoughtful experiments across multiple dimensions, and iteratively improve products based on rigorous analysis. Success in this role means navigating ambiguous problems where data might be incomplete or noisy, requiring both statistical rigor and creative modeling skills to generate actionable insights. The role demands close collaboration across engineering, product management, and business teams, suggesting a need for strong communication skills and influence, beyond just technical expertise. The qualifications emphasize a strong foundation in quantitative disciplines, coding proficiency (Python, R, SQL, and potentially C#), and experience in designing and interpreting A/B tests and time series analyses, underscoring the scientific rigor and responsiveness required. Given the scale and impact, the candidate will frequently face trade-offs between business needs and technical feasibility, needing sound judgment and innovative approaches to contribute meaningfully to product and business decisions. Early success is likely measured by the candidate’s ability to deliver reliable metrics, influence stakeholders through compelling data narratives, and embed robust, data-science driven workflows that improve the monetization platform.

Company Analysis:

Microsoft is a global technology leader committed to empowering individuals and organizations by fostering innovation and creating inclusive, impactful technology solutions. The company’s culture stresses a growth mindset, collaboration, and authenticity—values critical for a data scientist engaging with diverse teams and complex challenges. Operating across nearly 200 countries with a massive workforce, Microsoft blends scale with an entrepreneurial spirit, especially in its advertising business, which serves a dynamic, fast-evolving digital marketplace. This environment likely balances structured processes with opportunities for creativity, requiring employees to be adaptable and proactive. The company’s emphasis on inclusion and continuous learning means that this role will prosper if the candidate embraces feedback, challenges biases, and values diverse perspectives. Strategically, this position supports Microsoft's broader mission by enhancing the advertising platform's effectiveness, thus fueling revenue growth and customer satisfaction. The role’s influence can extend beyond immediate team boundaries, offering visibility with leadership and the chance to impact product strategy at a high level. Candidates should be prepared to engage deeply with cross-functional stakeholders and align their analytical initiatives tightly with Microsoft’s goals for innovation and market leadership.

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

• Behavioral: Tell me about a time when you had to design an experiment to measure the success of a new product feature. What challenges did you face and how did you ensure validity?
• Behavioral: Describe an instance where you had to communicate complex data insights to non-technical stakeholders. How did you tailor your message for impact?
• Behavioral: Share an experience where you challenged the status quo with a data-driven solution. What was the outcome and how was it received?
• Behavioral: How do you prioritize tasks when faced with multiple cross-team projects under tight deadlines?
• Technical: How would you approach defining and validating key performance metrics for a newly launched advertising product?
• Technical: Walk me through your process for designing and analyzing an A/B test on an advertising platform serving millions of users.
• Technical: What tools and techniques do you typically use for managing and analyzing structured versus unstructured data in your projects?
• Technical: Explain how you would handle time series analysis in the context of measuring advertising revenue trends.
• Situational: Imagine the data you receive is incomplete and noisy, but leadership needs quick insights. How would you proceed to provide actionable recommendations?
• Situational: You identify conflicting results between your analysis and an engineer’s implementation in the advertising system. How do you resolve this?
• Situational: If your data-driven recommendation is met with resistance by key product stakeholders, how would you influence them to consider your approach?
• Company Fit: Why are you interested in working on Microsoft Advertising specifically, given Microsoft's broader mission and values?
• Company Fit: How do your personal values align with Microsoft’s culture of growth mindset, inclusion, and innovation?
• Company Fit: Microsoft emphasizes collaboration across diverse teams. How have you successfully worked in such environments before?
• Questions for Interviewer: What are the biggest challenges currently facing the Microsoft Advertising Data Science Team?
• Questions for Interviewer: How does the team prioritize projects that balance long-term innovation with immediate business needs?
• Questions for Interviewer: How is success measured for the Data Scientist role within the first year here, beyond technical delivery?