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The Associate Director, Solutions will lead a client-facing team at YipitData, responsible for delivering bespoke analysis and data products, managing client experiences, and leveraging AI for operational efficiency.

Lead AI product strategy for investor workflows, designing AI-native products (agents, copilots, MCPs, APIs). Partner with investors, engineers, researchers, and designers to translate LLMs, retrieval, and agent architectures into reliable, production-grade features. Drive rapid experimentation, define evaluation and trust frameworks, and shape platform evolution for investor-grade AI products.

Design end-to-end UX for an AI-powered B2B data product. Translate complex AI and data concepts into intuitive, trustworthy interfaces; conduct user research; define workflows; collaborate with Product, Engineering, and Data Science; contribute to design systems and maintain design quality through launches.

Design, validate, and deploy scalable statistical and distributional models for enterprise consumer analytics. Implement rigorous methodologies, convert ad-hoc analyses into version-controlled analytical libraries, and partner with Data Engineering to optimize performance and scale compute workloads (including cloud/Databricks). Deliver reproducible analytics powering dashboards and LLM-driven applications, with a focus on panel and transaction-level consumer data.

Lead the Central Data Platform roadmap: define and prioritize capabilities, translate business needs into technical requirements, coordinate cross-functional execution, measure adoption and data quality, and drive continuous platform improvements to increase reuse and business impact.

Lead operational management of the Product Classification organization: hire, train, and scale classification and manual QA teams; set metrics, SLAs, and operating cadence; partner with Engineering and Product to improve LLM-driven classification; build processes, rules, and analytic checks to ensure high accuracy at scale.

The Product Manager will define and scale a quant platform for alternative datasets, collaborate with teams to develop product specifications, conduct customer research, and manage go-to-market strategies.

The Data Product Analyst will own Signals data products, work with AI and Data Engineering, ensure data quality, conduct analyses, and shape product improvements through client feedback.

Manage and grow enterprise Technology/Cloud accounts by owning renewals, driving upsells and cross-sells, building executive relationships, coordinating with Solutions/Product teams, maintaining pipeline/forecast in CRM, and meeting revenue and retention targets.

Own and maintain the Kepler consumer transactions feed end-to-end: ensure data accuracy, refine methodologies, implement QA frameworks, prototype enhancements, use SQL/Python/PySpark and AI tooling to automate workflows, and collaborate cross-functionally to resolve high-complexity issues for clients.