Data Operations Analyst

Company Overview

YipitData is the leading market research and analytics firm for the disruptive economy and most recently raised $475M from The Carlyle Group at a valuation of over $1B. Every day, our proprietary technology analyzes billions of alternative data points to uncover actionable insights across sectors like software, AI, cloud, e-commerce, ridesharing, and payments. Our data and research teams transform raw data into strategic intelligence, delivering accurate, timely, and deeply contextualized analysis that our customers—ranging from the world’s top investment funds to Fortune 500 companies—depend on to drive high-stakes decisions. From sourcing and licensing novel datasets to rigorous analysis and expert narrative framing, our teams ensure clients get not just data, but clarity and confidence. We operate globally with offices in the US (NYC, Austin, Miami, Mountain View), APAC (Hong Kong, Shanghai, Beijing, Guangzhou, Singapore), and India. Our award-winning, people-centric culture—recognized by Inc. as a Best Workplace for three consecutive years—emphasizes transparency, ownership, and continuous mastery.

Position Summary

The Data Operations Analyst plays a critical role in developing custom product attribution based on unique customer needs. Each of our corporate retail and brand customers thinks about the structure of their categories in slightly different ways, and the Data Operations Analyst will execute the mapping of products to their requirements using a combination of manual tagging and machine learning tools. Interpretation and execution design require strong judgment. The ideal candidate should bring a combination of technical skills, knowledge of consumer product data, strong attention to detail, and accountability to plan and deliver projects on time with a high degree of accuracy.

Key Responsibilities

• Work with corporate retail and brand customers to understand their category structures and product attribution requirements.
• Execute the mapping of products to customers' category needs, utilizing both manual tagging and machine learning tools.
• Apply strong judgment and interpretation skills to ensure that data mapping aligns with customer specifications and business goals.
• Collaborate with cross-functional teams to plan and deliver projects on time, ensuring high levels of accuracy and precision.
• Continuously monitor and improve product attribution processes to increase efficiency and quality.
• Leverage technical skills to enhance existing processes and tools that support data operations.
• Maintain strong attention to detail and ensure accuracy in every aspect of the data mapping process.
• Take accountability for successfully executing projects, including meeting deadlines and client expectations.

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