AirOps is looking for a Data Scientist to design and implement advanced NLP workflows that turn large-scale, unstructured data into actionable insights about brand visibility.
Requirements
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
Responsibilities
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
Other
Comfort operating in fast-paced, ambiguous environments where you ship quickly and iterate
Equity in a fast-growing startup
Competitive benefits package tailored to your location
