Collaborate with the CTO and senior leadership to scope, prioritize, and deliver AI and data science innovation projects aligned to business and product strategy.
Define and execute our AI strategy, transforming complex business challenges into data science-driven solutions that evolve from prototypes into scalable, production-grade AI services.
Modernize data infrastructure and deploy impactful AI capabilities including generative AI, agentic AI, and deep learning. Each tightly aligned with measurable business outcomes.
Own the end-to-end lifecycle of AI initiatives from greenfield concept through prototyping, experimentation, and implementation into successful market-ready solutions.
Rapidly evaluate new AI/ML techniques, architectures, and technologies for practical application.
Champion responsible AI practices, including transparency, bias mitigation, and model governance.
Lead and mentor a small founding team, setting the tone for a culture of innovation, experimentation, and rapid iteration.
Establish technical best practices in experimentation, data pipelines, model development, and deployment, building the foundation for future growth.
Foster organizational best practices by bridging data science, engineering, and product teams to embed AI across business functions, ensuring alignment through transparent communication and cross-functional collaboration.
Inspire and develop future team members as the group expands.
Partner with product managers to shape AI product strategies and make build-vs-buy decisions.
Provide clear communication and insights to senior executives and stakeholders.
Represent the AI/Data Science team in strategic forums, highlighting impact and progress.
Requirements
Experience 12+ years in technology roles with at least 7+ years focused on data science/AI.
5+ years in leadership roles managing high-performing data science or AI teams.
Proven track record of delivering greenfield AI/ML solutions into production environments.
Experience in rapid prototyping, experimental design, and scaling AI systems.
Deep knowledge of machine learning, natural language processing, generative AI, and modern data/ML architectures.
Strong grounding in software engineering practices, data pipelines, and MLOps.
Hands-on ability to contribute to early prototypes alongside a small team.
Excellent communication skills with the ability to explain AI concepts to both technical and non-technical audiences.
Demonstrated ability to lead in ambiguous, fast-paced, and experimental environments.
Strong experience balancing near-term delivery with long-term technical strategy.
Familiarity with lean product development and design thinking.
Experience working in startup, innovation lab, or 0→1 product environments.
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