> Markdown version of [/jobs/ext/3020657-head-of-data-science](https://www.wearedevelopers.com/jobs/ext/3020657-head-of-data-science). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Head of Data Science - **Company:** Stealth Startup - **Location:** Seattle, WA, United States (Remote available) - **Experience:** Expert - **Salary:** $170,000.0 - $200,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, C Sharp (Programming Language), Computer Programming, Python (Programming Language), Machine Learning, Named Entity Recognition, Large Language Models, Model Validation, Generative AI, Production Code, Data Analytics, Build Tools, Machine Learning Operations, Golang - **Published:** September 21, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/plrdyvytme ## About the Role * 5+ years of experience in data science, machine learning, applied ML, or a related field. * Strong programming skills in Python, Go, C#, or a similar language. * Experience building production-quality tools and systems rather than only notebooks and prototypes. * Experience designing and implementing evaluation frameworks for ML or AI systems, including generative AI systems where correctness is difficult to measure using simple automated metrics. * Hands-on experience with LLM-based systems, including model evaluation, experimentation, retrieval, embeddings, or fine-tuning. * Strong understanding of statistical methods, experimental design, and quantitative analysis. * Ability to turn ambiguous product or technical problems into concrete experiments, implementations, and measurable outcomes. * Ability to work independently as the first specialist establishing a new technical discipline. * Willingness and ability to work within HIPAA requirements and the constraints associated with protected health information. * Ability to quickly learn and operate within the healthcare domain. Nice to Have * Experience with clinical NLP, medical coding, or healthcare revenue cycle workflows. * Experience working with clinical, healthcare, regulated, or other sensitive data. * Experience working with structured and unstructured healthcare data. * Experience applying AI/ML to clinical or healthcare workflows. ## Description We are seeking a Head of Data Science to become our first dedicated Data Science hire. Reporting directly to the CTO, you will work closely with Engineering and Product to improve the accuracy, reliability, and measurability of our AI-powered systems. This is a hands-on technical leadership role. You will work directly with data and models, write production-quality code, build evaluation and experimentation infrastructure, and investigate issues in production. You will own the Data Science function from the ground up, defining its technical direction, establishing priorities, and determining the staffing and infrastructure needed as we grow. Key Responsibilities * Design and implement evaluation frameworks for our AI pipelines, including automated and human evaluation of clinical accuracy, completeness, consistency, and other domain-specific metrics. * Build systems and processes for collecting, labeling, and incorporating provider feedback and real-world usage data into model and product improvements. * Develop experimentation tools and processes for evaluating prompts, models, retrieval strategies, and other AI system changes. * Define model and technical strategy, including selecting and benchmarking models and determining when prompting, retrieval, fine-tuning, PEFT/LoRA, preference tuning, or other approaches are appropriate. * Combine LLMs with classical ML and statistical techniques such as entity extraction, assertion and negation detection, embeddings, and retrieval when they improve accuracy, cost, latency, or reliability. * Partner with engineers to build reliable production systems incorporating data science and ML techniques, including structured outputs, confidence scoring, and validation layers. * Establish practical development standards for reproducible experiments, model evaluation, monitoring, and production reliability. * Investigate production issues and identify data-driven opportunities to improve AI system performance. * Partner with Product to identify high-value opportunities for applying data science and machine learning to new clinical workflows and specialties. * Define the future structure, priorities, and staffing needs of the Data Science function as we scale., Within the first six months, you will establish a rigorous, measurable approach to evaluating and improving our AI systems. Success will include: * Building an automated evaluation suite that can gate releases of our AI pipelines. * Establishing a clinician feedback loop that turns real-world feedback, edits, and corrections into measurable quality improvements. * Creating systematic experimentation processes for models, prompts, retrieval strategies, and other AI changes. * Providing data-driven insight into what works, what does not, and why. * Defining the next priorities, infrastructure, and staffing requirements for our Data Science function. You will serve as the technical owner of Data Science while remaining deeply involved in hands-on implementation and day-to-day technical work. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Go with the Flow: Stop the Leaks Before Your Memory's a Waterfall!](https://www.wearedevelopers.com/videos/100073-go-with-the-flow-stop-the-leaks-before-your-memory-s-a-waterfall) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Your imaginations is (no longer) the limit: how Generative AI empowers people to be creative](https://www.wearedevelopers.com/videos/741-your-imaginations-is-no-longer-the-limit-how-generative-ai-empowers-people-to-be-creative) - [AI in High-Stakes Industries: Lessons Learned](https://www.wearedevelopers.com/videos/100253-ai-in-high-stakes-industries-lessons-learned) - [Scoring 2000 Products per Request: Performance Pitfalls in Golang](https://www.wearedevelopers.com/videos/2073-scoring-2000-products-per-request-performance-pitfalls-in-golang) ## Related Articles - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [How to start an AI project for a good cause and boost your career](https://www.wearedevelopers.com/magazine/15-how-to-start-an-ai-project-for-a-good-cause-and-boost-your-career)