> Markdown version of [/jobs/ext/2704705-full-stack-data-scientist](https://www.wearedevelopers.com/jobs/ext/2704705-full-stack-data-scientist). 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).

---

# Full Stack Data Scientist

- **Company:** Bayesian Health, Inc.
- **Location:** United States (Remote available)
- **Experience:** Starter
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Data Mapping, Software Debugging, Python (Programming Language), Machine Learning, Software Product Management, Standard Sql, Machine Learning Operations
- **Published:** September 4, 2026
- **Apply:** https://startup.jobs/staff-machine-learning-engineer-bayesian-health-inc-8137869

## About the Role

* Ph.D. in a relevant field plus 3+ years relevant experience, or a relevant Master's degree and 5+ years experience shipping ML based software products.
 * Experience owning your ML models from prototyping to production.
 * Experience writing production-grade Python and SQL code to implement and evaluate ML models in production systems.
 * Experience using MLOps tools such as SageMaker and MLFlow., * Experience going 0-1 and shipping high impact AI/ML products.
 * Experience building solutions within healthcare and/or familiarity working with messy health data.
 * Experience working with enterprise customers, and the agility and responsiveness they require.
 * Comfortable interpreting / leveraging state-of-the-art peer-reviewed methods or tools in designing your approach.
 * Excitement for Bayesian's mission and being a bar raiser so we can accelerate the pace at which we create value.

## Description

* Part Data Scientist (building models), part Applied Scientist (productionizing models), and part MLE (deploying, maintaining), also known as "Full Stack Data Scientist" - someone who wants to own the end-to-end effectiveness of their real-time models in a live, clinical AI product., As a Staff Machine Learning Engineer, you are not satisfied with training and tuning ML models that predict clinical conditions in patients; you also want to own the effectiveness of your model in the real world. In practice, that means you aren't afraid to get your hands dirty by writing data mapping code, debugging a specific patient case by following patient data as it moves through our AWS services, or improving the timeliness of your model's predictions by reading and writing production-grade Python and SQL code., * Model Prototyping: Develop and tune innovative, new ML models and labeler systems based on deep understanding of clinical use cases and state-of-the-art ML methods.
 * Productionizing: The same models that you develop with production-grade python.

 * Deploying: Identify strategies for improving our production ML-based systems, and write, debug, and deploying production-grade Python code to implement those strategies.
 * MLOps: Build infrastructure that enables ML model development and deployment in production systems.


## Related Videos

- [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning)
- [How building an industry DBMS differs from building a research one](https://www.wearedevelopers.com/videos/768-how-building-an-industry-dbms-differs-from-building-a-research-one)
- [Web-based Information Visualization](https://www.wearedevelopers.com/videos/84-web-based-information-visualization)
- [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail)
- [Why Your AI Agent Keeps Hallucinating Your Data: Building Deterministic Context Layers](https://www.wearedevelopers.com/videos/2055-why-your-ai-agent-keeps-hallucinating-your-data-building-deterministic-context-layers)
- [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology)

## Related Articles

- [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)
- [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production)
- [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers)
- [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)
- [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)