Today thousands of leading brands and agencies use AirOps to win the battle for attention with content that both humans and agents love.
We’re building the platform and profession that will empower a million marketers to become modern leaders — not spectators — as AI reshapes how brands reach their audiences.
We’re backed by awesome investors, including Unusual Ventures, Wing VC, Founder Collective, XFund, Village Global, and Alt Capital, and we’re building a world-class team with in-person hubs in San Francisco, New York, and Montevideo, Uruguay.
We’re hiring a Data Scientist to design and implement advanced NLP workflows that turn large-scale, unstructured data into actionable insights about brand visibility. You will work on tasks such as text processing, entity extraction, clustering, and semantic search, as well as develop the analytical models that power these capabilities. Your work will power ML-driven capabilities in the AirOps platform and give customers deeper, data-backed insights into their brand visibility across AI-driven channels.
Build and maintain NLP workflows for processing unstructured text, including embeddings, entity extraction, and classification
Develop clustering, semantic search, and pattern detection methods to uncover insights in large datasets
Analyze large, multi-source datasets to identify trends, measure brand visibility, and surface actionable insights for customers
Evaluate and refine NLP techniques using quantitative metrics and real-world performance data
Ensure data quality through preprocessing, feature engineering, and rigorous validation
Collaborate with data engineers to integrate NLP and analytical solutions into production pipelines
Partner with product and engineering teams to translate business needs into scalable, data-driven solutions
Monitor and iterate on performance of deployed solutions to ensure ongoing accuracy and relevance
4+ years of experience in data science, applied NLP, or analytics, ideally in AI, SaaS, or data-intensive products
Strong fluency in Python and SQL, with experience manipulating and analyzing large datasets
Hands-on experience with NLP libraries and frameworks such as Hugging Face, spaCy, or LangChain, and familiarity with LLM-based workflows
Proven ability to extract insights from complex, multi-source datasets and communicate findings clearly to both technical and non-technical audiences
Understanding of clustering, semantic search, and related ML techniques
Experience with data warehouses and OLAP databases (e.g., Redshift, Snowflake, BigQuery, ClickHouse)
Familiarity with data preprocessing, feature engineering, and validation techniques to ensure data quality
Comfort operating in fast-paced, ambiguous environments where you ship quickly and iterate
Extreme Ownership
Quality
Curiosity and Play
Make Our Customers Heroes
Respectful Candor
Equity in a fast-growing startup
Competitive benefits package tailored to your location
Flexible time off policy
Generous parental leave
A fun-loving and (just a bit) nerdy team that loves to move fast!
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