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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - **Company:** The Joule - **Location:** Minneapolis, MN, United States - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Artificial Neural Networks, Nvidia CUDA, Continuous Integration, Data Cleansing, Github, Python (Programming Language), Machine Learning, Object-Oriented Software Development, Performance Tuning, Tensorflow, Software Engineering, Unstructured Data, Jupyter Notebook, Feature Engineering, Sql Optimization, Pytorch, Flask (Web Framework), Large Language Models, Model Validation, Generative AI, Git, Fastapi, Pytest, Containerization, Gitlab-ci, Scikit Learn, Integration Tests, Information Technology, Statistics Packages, Xgboost, Machine Learning Operations, TensorRT, Restful APIs, Software Version Control, Docker, Microservices - **Published:** September 11, 2026 - **Apply:** https://www.thejobnetwork.com/job/a68e2f26-efa5-4c9e-ad09-e1864e9206aa/data-scientist ## About the Role * 5-7+ years of progressive professional experience designing, shipping, and maintaining complex ML/AI solutions in enterprise production environments. * Experience building and deploying machine learning models in a production environment. * Strong practical experience with core ML algorithms (scikit-learn, XGBoost, LightGBM, statsmodels, PyTorch, or TensorFlow). * Demonstrated capability in writing clean, PEP 8-compliant, modular, and object-oriented Python code (beyond Jupyter notebooks). * Experience using automated testing frameworks (pytest, unittest) and writing unit/integration tests. * Hands-on experience developing RESTful APIs using frameworks like FastAPI or Flask. * Familiarity with containerization technologies (Docker) and version control workflows (Git, GitHub Actions, or GitLab CI/CD). * Advanced SQL proficiency and experience querying structured and unstructured datasets. * Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Applied Mathematics, or a related quantitative field. Preferred Qualifications: * Generative AI & Enterprise LLMs: Hands-on experience developing, fine-tuning (LoRA/QLoRA), or deploying proprietary Large Language Models (LLMs), agentic frameworks, custom embeddings, or enterprise RAG systems. * Experience with GPU acceleration frameworks (CUDA, TensorRT, vLLM, Ollama). * Demonstrated leadership in mentoring teams and defining enterprise data and AI governance policies. ## Description Job Title: Data Scientist Location: Minneapolis, MN Job Summary: System One is seeking a Data Scientist with 5+ years of hands-on experience to design, build, and deploy production-grade machine learning models. In this role, you will bridge the gap between traditional data science and software engineering by writing clean, modular Python code to build robust AI capabilities embedded directly into our enterprise products and systems. Responsibilities * Design, train, and validate traditional predictive and analytical machine learning models (regression, classification, decision trees, time-series, and neural networks). * Write scalable, production-grade Python code to wrap models into microservices and expose them via RESTful APIs for real-time inference. * Build and maintain automated data preprocessing, feature engineering, and model evaluation pipelines using CI/CD and MLOps best practices. * Track model performance, data drift, and latency in production, ensuring reliability and accuracy over time. * Collaborate directly with executive leadership, product directors, and enterprise architects to define the AI/ML product roadmap. ## Related Videos - [Developer Experience, Platform Engineering and AI powered Apps](https://www.wearedevelopers.com/videos/990-developer-experience-platform-engineering-and-ai-powered-apps) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [Bringing AI Model Testing and Prompt Management to Your Codebase with GitHub Models](https://www.wearedevelopers.com/videos/1536-bringing-ai-model-testing-and-prompt-management-to-your-codebase-with-github-models) ## Related Articles - [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 And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering)