About the job
Join Peec as our Director of Data Science!
At Peec, we are on a mission to revolutionize AI-driven search recommendations. We are seeking an experienced Director of Data Science to lead our talented team, drive innovation, and develop cutting-edge machine learning solutions that will define the future of our products.
Your Responsibilities
Lead, mentor, and inspire a high-performing data science team, effectively communicating complex technical concepts to stakeholders including executives, customers, and partners.
Design, implement, and manage the machine learning models that enhance Peec’s AI Search recommendations, taking ownership of our critical ML systems.
Innovate and develop state-of-the-art algorithms that dissect AI search and LLM behavior, translating deep technical knowledge into competitive advantages for our customers.
Oversee the entire ML lifecycle, from foundational research and rigorous testing to deployment, monitoring, and constant enhancement.
Architect scalable data and ML systems, making impactful decisions regarding data pipelines, modeling methodologies, evaluation processes, and model deployment.
Write and review high-quality production code, establishing a technical standard for the organization.
Your Qualifications
Minimum of 8 years of professional experience in data science, with at least 3 years in a leadership position at a high-growth startup or a top-tier tech company (e.g., Tech Lead, Engineering Manager, or Software Development Manager).
A proven leader in data science with a unique blend of technical expertise and proven track record of delivering impactful ML products in dynamic environments.
Experience in owning and scaling complex ML systems from initial research ideas to reliable, high-impact production solutions.
Exceptional proficiency in Python and applied machine learning with a strong understanding of APIs, data pipelines, ML infrastructure, and production reliability.
A solid, foundational understanding of LLMs and AI search systems, with the capability to critically analyze, reverse-engineer, and reason about model behaviors.
Track record in making significant decisions that drive data science initiatives forward.
