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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist (Databricks, Mosaic AI) - **Company:** Open Data Watch, Inc. - **Location:** Alexandria, VA, United States (Remote available) - **Experience:** Experienced - **Salary:** $110,000 - $140,000 - **Contract:** Permanent contract - **Skills:** Microsoft Excel, Artificial Intelligence, Amazon Web Services, Microsoft Azure, Programming Tools, Machine Learning, Microsoft PowerPoint, OpenAI, Azure Machine Learning, Search Technologies, SQL Databases, Management of Software Versions, Feature Store, Feature Engineering, Large Language Models, Google Vertex AI, Model Validation, Agentic-AI, Git, Pandas, Pyspark, Scikit Learn, Data Management, Machine Learning Operations, Drift Detection, Software Version Control, Databricks - **Published:** November 3, 2026 - **Apply:** https://www.careerbuilder.com/job-details/data-scientist-databricks-mosaic-ai-alexandria-va--5d998a5c-e46f-4c34-9a30-857797aa5da2 ## About the Role Data Science, Artificial Intelligence (AI), Public Company Accounting Oversight Board (PCAOB), Artificial Intelligence (AI), Securities and Exchange Commission (SEC), Defense Contract Audit Agency (DCAA), Government, Problem Solving Skills, Customer Training, Leadership, * 4+ years of data science or machine learning engineering experience, including models deployed to production * Bachelor's degree * Python for data science and machine learning, including pandas, scikit-learn, and PySpark * Hands-on Azure Databricks work, including MLflow for experiment tracking and model management * Deploying and monitoring models in production, including model serving, versioning, and drift monitoring * Building LLM applications, including retrieval-augmented generation (RAG) * Evaluating model and LLM output against defined metrics, test sets, and human review * Structured Query Language (SQL) and Git-based version control * Delivery experience in a federal government environment, working to its security, access, and review processes * Proficiency in writing, PowerPoint, and Excel * United States citizenship; dual citizenship and green card holders are prohibited by the contract terms * The ability to satisfy the required suitability, security, and access requirements Preferred * Experience on a federal system accredited at Impact Level 5 (IL-5) or higher * Agent Bricks, Databricks AI Search (formerly Vector Search), or MLflow 3 evaluation for generative AI * Experience with a second managed machine-learning platform, such as Azure Machine Learning, Amazon SageMaker, or Google Vertex AI * Azure OpenAI or other models in Microsoft Foundry * Databricks certification, or a Microsoft Azure AI or data science certification * Model risk management or model validation experience, including the documentation a model review asks for * Familiarity with artificial intelligence (AI)-assisted developer tooling Who you are You care whether a model works, not only whether it trains. You define what good looks like before you build, test against it, and say so when a model is not ready. You experiment, fail, learn, and repeat quickly. You would rather own an outcome than be handed a task. What you bring * Hands-on machine learning on Azure Databricks, including MLflow, feature engineering, and model serving. * Working experience building LLM applications, including retrieval and evaluation. * The evaluation discipline that production models demand, including test sets, metrics, and monitoring. You adapt your development workflow as AI tools evolve, using them to help implement, test, and improve the components you own. You give the tools clear context, review and test their output, and remain accountable for the code you deliver. When we talk Be prepared to discuss a difficult problem you worked through, the decisions you made, what happened, and what you learned. ## Description Your first project will likely have you taking models and AI agents from experiment to production on Azure Databricks, with the evaluation evidence to show they work. Depending on the assignment, you may: * Develop and train machine learning models on Azure Databricks, tracking experiments, models, and versions in MLflow. * Build reusable features in the Databricks Feature Store, and serve models through Databricks Model Serving. * Build retrieval and agent applications with Agent Bricks and Databricks AI Search (formerly Vector Search), using Azure OpenAI models through Microsoft Foundry. * Evaluate model and agent quality with MLflow evaluation, including large language model (LLM) judges, labeled test sets, and human review. * Monitor models in production for drift and quality, and write the documentation a model review asks for. You deliver models the agency can trust and explain. You measure quality before and after release, record what each model is for and where it fails, and leave the team pipelines it can retrain and rerun without you., You will work alongside developers, engineers, data scientists, architects, and strategists, on work ranging from strategy to implementation. We support your development across assignments and clients through extensive onboarding, sponsored professional certifications such as the Data Management Capability Assessment Model (DCAM) and Amazon Web Services (AWS) technical certifications, and rotation across functions to expand your skills and perspective. The mission is real, the problems are hard, and you own what you ship.