Okay, I've searched for Data & Analytics Lead roles in New York, NY requiring 6+ years of experience, advanced Python and SQL skills, expertise in marketplace or retail analytics, and full-time positions. I have found 47 positions for you.

Sure. Here's the analysis:

Job Analysis:

The Data & Analytics Lead at RepRally is fundamentally hired to architect and lead the company's data-driven decision-making engine, translating complex marketplace dynamics into actionable insights that power strategic business initiatives. This role demands not only building robust, scalable data infrastructure but also embedding intelligence into multi-sided marketplace operations—connecting brands, sales reps, and retailers. The candidate will need to create and refine machine learning models (for sales prediction, pricing optimization, brand-store matching), develop routing and territory optimization algorithms to enhance field sales efficiency, and define critical health metrics that reflect the marketplace’s economic vitality. Success here means the ability to convert large-scale, fragmented data into strategic guidance for leadership, directly influencing product development, pricing strategy, and market expansion. The ideal candidate must be technically fluent in advanced Python for production-grade ML, expert in SQL handling big datasets, and experienced in modern data stack tools like Snowflake, dbt, and Metabase. Beyond technical skills, the role requires executive presence, the ability to work with ambiguity, and strong communication skills since they will regularly present complex insights to leadership and influence cross-functional stakeholders. Autonomy and strategic judgment are key—whether interpreting marketplace signals, driving metric frameworks, or building predictive models. Early success will be measured by establishing a reliable data infrastructure, delivering insights that impact key KPIs such as GMV and liquidity, and enabling smarter operational decisions across the organization.

Company Analysis:

RepRally is a high-growth Series A startup positioned as a disruptor in the $1.5 trillion wholesale commerce industry, aiming to replace antiquated processes with a unified digital platform. Its market position as a transformative player means the company operates in a fast-paced, innovation-driven environment where moving quickly and iterating is essential. The culture reflects a premium on ownership, craftsmanship, and delivering impact, with a team composed of experienced operators from successful marketplaces and consumer brands. This environment suggests the Data & Analytics Lead will thrive with a startup mindset: comfortable with rapid change, ambiguity, and hands-on collaboration. The role sits at the core of the company’s strategic engine, working closely with the CEO and leadership, which gives it high visibility and direct influence on business-critical decisions. Being an early data hire, the person will shape not just analytics outputs but overall data culture and infrastructure, aligning closely with RepRally’s mission to innovate wholesale distribution. The in-office, NYC-based setting supports deep team integration, signaling that interpersonal skills and cultural fit are as important as technical acumen. Overall, this is a strategic hire aimed at scaling operations through data intelligence, supporting RepRally’s rapid growth trajectory and marketplace leadership ambitions.

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

• Behavioral: Tell me about a time when you had to build a data infrastructure from scratch. What challenges did you face, and how did you overcome them?
• Behavioral: Describe an experience where you influenced leadership decisions through data insights. How did you ensure your message was understood and acted upon?
• Behavioral: Share a situation where you navigated ambiguity in a fast-paced environment. How did you prioritize your tasks and maintain effectiveness?
• Behavioral: Can you give an example of how you worked cross-functionally to solve a complex business problem involving multiple stakeholders?
• Technical: How would you approach designing a machine learning model to optimize pricing in a dynamic, multi-sided marketplace?
• Technical: Explain your experience with building routing or territory optimization algorithms. What factors do you consider critical in such models?
• Technical: Walk me through how you would structure a data pipeline using Snowflake, dbt, and Metabase to support real-time business metrics.
• Technical: How do you validate and monitor the performance of predictive models in production environments?
• Situational: Imagine a scenario where key sales metrics suddenly drop and your data shows conflicting signals. How would you investigate and communicate your findings?
• Situational: If leadership asks you to prepare a business review with limited clean data and tight deadlines, what steps would you take to ensure quality insights?
• Situational: You're asked to partner with the CEO on a new market expansion strategy that requires quick analytical support. How do you balance speed with accuracy?
• Company Fit: What attracts you to RepRally’s mission to transform wholesale commerce, and how do you see yourself contributing to that vision?
• Company Fit: How do your values align with a culture that emphasizes ownership, craftsmanship, and impact?
• Company Fit: Given RepRally’s fast-paced startup environment and emphasis on in-person collaboration, how do you envision adapting your work style?
• Questions to Ask: How does the leadership team envision the evolution of data and analytics at RepRally over the next 12-18 months?
• Questions to Ask: Can you describe how cross-functional teams currently collaborate and how you see the Data & Analytics Lead facilitating these interactions?
• Questions to Ask: What are the biggest challenges RepRally faces in building and scaling its three-sided marketplace, and how can data analytics help address them?