Vice President, Data Science

Role overview

Lead and grow an applied data science organization whose research, experimentation, and modeling work directly powers production AI products for customer experience use cases. The role combines executive leadership with hands-on technical contribution, setting methodology across LLM evaluation, fine-tuning, prompt design, and composite AI architectures while scaling the team and serving as a public-facing voice for the discipline.

Responsibilities

- Define technical direction for applied AI and data science, including research roadmaps, experimental design, model evaluation frameworks, and the processes used to move work from prototype into product. - Contribute hands-on to a portion of the technical workload—fine-tuning, prompt engineering, architecture selection, or evaluation—while overseeing the broader team's output. - Recruit, develop, and scale the data science organization across multiple geographies to meet growing demand. - Partner cross-functionally with product, engineering, and executive stakeholders, translating technical outcomes into product and business impact. - Meet occasionally with customers to understand product impact and represent the data science function externally through blog posts, papers, conference talks, and other industry engagement. - Build operational structures for experimentation, data quality, model governance, and continuous delivery of data science innovation.

Requirements

- 12+ years in data science or applied AI research, with significant experience in a leadership capacity at a top-tier applied research organization. - Deep, hands-on expertise with LLMs, agentic architectures, retrieval-augmented generation, transformers, and composite model pipelines. - Strong command of commercial and open-source model ecosystems, with proven ability to benchmark, compare, and select models for real-world use cases. - Experience designing evaluation frameworks, experiment methodologies, fine-tuning workflows, prompt engineering, and model orchestration for production systems. - Proficiency in large-scale data collection, labeling, curation, and governance, ideally with conversational or unstructured text data. - Advanced degree (PhD or Master's with substantial industry experience) in Computer Science, Machine Learning, AI, Statistics, Applied Mathematics, Electrical Engineering, Computational Linguistics, or a related field.

Nice to have

- Track record of building and scaling high-performing data science organizations across geographies. - Executive presence with the ability to influence senior leadership and defend technical decisions. - Familiarity with responsible AI, privacy considerations, and model safety at enterprise scale.

Benefits and work setup

- Remote-first for candidates outside a 30-mile radius of an office; hybrid (3 days in office Tuesday–Thursday) for those within range. - US base salary range of $233,000–$512,000, with additional annual performance bonus, stock, and other applicable incentive plans. - Health, dental, and vision coverage starting day one, with employer-paid employee premiums and shared dependent costs, plus short- and long-term disability and basic life insurance. - 401(k) with employer matching, employee stock purchase plan, paid time off, company holidays, paid volunteer hours, and 12 weeks of paid parental leave. - Access to a mental health support platform offering therapy, coaching, and self-guided mindfulness resources.