
Data Scientist
Posted Aug 13

Posted Aug 13
This is a fully remote position, open to applicants in United States.
β’ Develop and enhance the rules, heuristics, and models that drive model and provider routing systems.
β’ Create analytical products and perform in-depth analyses to assist users in understanding usage, diagnosing issues, and optimizing workflows.
β’ Design and deliver user-facing data features, which include task-type classification taxonomies and public rankings of model performance.
β’ Establish and monitor product metrics such as feature adoption, user engagement, and overall platform health.
β’ Connect insights to the product roadmap and architectural decisions.
β’ Contribute to the foundational elements of the dbt and ClickHouse data warehouse.
β’ Collaborate with customer-facing, engineering, and product teams to transform insights into delivered features.
β’ Manage analytical inquiries from beginning to end, including problem framing, data exploration, and final delivery.
β’ Proven experience in building and deploying production-level data products, including models, algorithms, classifiers, scoring systems, or automated processes.
β’ Capability to collaborate with engineering and product teams to translate insights and analytics into customer-facing features.
β’ Strong proficiency in SQL, including the ability to write complex and efficient queries on large-scale analytical databases such as ClickHouse or BigQuery.
β’ Extensive knowledge of AI and agents, encompassing model evaluation, prompt engineering, and the agentic ecosystem.
β’ Solid statistical and mathematical background in distributions, causal inference, and experimental design.
β’ Proficiency in Python or a similar scripting language for model prototyping, running simulations, and constructing data pipelines.
β’ At least 4 years of relevant experience in data science, applied machine learning, or quantitative product roles at a high-growth company.
β’ Product-oriented mindset with a strong sense of product development.
β’ Ability to work autonomously in fast-paced, low-structure environments.
β’ Extensive use of coding agents, MCP servers, and modern AI technologies.
β’ Strong problem-solving skills and the ability to navigate uncertainty.
β’ Excellent written communication skills for both technical and non-technical audiences.
β’ Experience with LLM evaluation and benchmarking, developer platforms, APIs/SDKs, usage-based products, NLP, machine learning engineering, or TypeScript is a plus.
β’ Equity offered
Pyyne
Pursuit Aerospace
Pursuit Aerospace
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