Top Tech Jobs & Startup Jobs in Austin, TX

Own the conversion of raw alternative datasets into scalable, AI-ready data products. Define methodologies, metric definitions, and guardrails for AI-driven insights. Partner with engineering, product, and customers to expand use cases, ensure data quality, validate changes, and manage incidents to deliver reliable, explainable data products at scale.

The Senior Recruiter will lead high-impact recruiting efforts for the GTM organization, focusing on strategic searches across Sales, Marketing, Customer Success, and Strategy. Responsibilities include managing the full recruiting cycle, developing talent pipelines, enhancing candidate experience, and utilizing ATS systems effectively.

The Client Strategy Manager will manage client relationships, develop commercial strategies, and ensure client success through proactive engagement and support. This role includes account management, upselling, and enhancing client engagement with the firm's analytics services.

Lead an end-to-end data domain: define processing and validation, build reusable methodologies and QA/monitoring systems, partner with product and engineering to set technical direction, onboard new datasets, apply AI/automation to reduce manual work, and mentor junior analysts to scale domain capabilities.

Own and maintain data products end-to-end for sector teams, analyze large datasets, refine methodologies, automate workflows using AI and tooling, collaborate with Research, Engineering, and Product, and deliver accurate, client-facing insights and improvements.

Assess and evaluate third-party datasets, define success metrics and analytical frameworks, run quantitative analyses, and recommend product opportunities. Support new product development, collaborate cross-functionally with engineering and partnerships, leverage AI/LLMs and automation, and contribute to tooling, knowledge, and operational efficiency.

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.

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.

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.