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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist (Looker / AI / BI) - **Company:** Northramp LLC - **Location:** Washington, DC, United States (Remote available) - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** A/B Testing, Artificial Intelligence, Amazon Web Services, Data Analysis, Computer Vision, BigQuery, Cloud Database, Software Documentation, Data Visualization, Document-Oriented Databases, Statistical Hypothesis Testing, Python (Programming Language), Machine Learning, Natural Language Processing, NumPy, Power BI, Cloud Services, Tensorflow, Azure Machine Learning, Software Engineering, SQL Databases, Tableau (Software), Data Processing, Business Intelligence Development Studio, Google Cloud, Cloud Platform System, Feature Engineering, Pytorch, Delivery Pipeline, Pandas, Build Management, Scikit Learn, Information Technology, Data Analytics, Machine Learning Operations, Looker Analytics, Software Version Control - **Published:** May 23, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=eb55a72d2bd135c4 ## About the Role Do you have experience in Time series models?, Do you have a Master's degree?, You turn data into decisions that program managers and agency leaders actually act on. You know when to reach for a simple statistical model and when the complexity of ML is actually warranted, and you've delivered BI solutions that get used rather than ignored. You communicate findings clearly to non-technical stakeholders and you operate with rigor around data quality and reproducibility., * 3 to 6 years of progressive, hands-on experience in data science or applied analytics with production model deployment experience. * Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative field. * Proficiency in Python for data science (pandas, NumPy, scikit-learn, statsmodels) and SQL for data extraction and analysis. * Hands-on experience with Looker - LookML modeling, dashboard development, and content management. * Experience training, validating, and deploying machine learning models in cloud environments (Vertex AI, SageMaker, or Azure ML). * Strong grounding in statistical methods: regression, classification, time series analysis, and A/B testing. * Working knowledge of BigQuery or equivalent cloud data warehouses for large-scale analytical workloads. * Experience with data visualization best practices and BI tooling beyond Looker (e.g., Tableau, Power BI, or Google Looker Studio). * Familiarity with MLOps principles: model versioning, experiment tracking (MLflow or Vertex AI Experiments), and deployment pipelines. * Understanding of federal AI governance guidance (OMB M-24-10 or equivalent) and FedRAMP data handling requirements. * U.S. Citizenship and the ability to obtain and maintain a DHS suitability / Public Trust clearance., * Google Cloud Professional Machine Learning Engineer or equivalent AWS/Azure ML certification. * Looker certification or demonstrated advanced LookML experience. * Security+ or equivalent certification. * Experience with NLP, computer vision, or generative AI application development. * Federal data science or analytics program experience. * Active Public Trust or higher clearance. Clearance DHS suitability and a Public Trust background investigation are required for this role. Active Public Trust or higher clearance is preferred. Selected applicants will be subject to a security investigation and may need to meet eligibility requirements for access to controlled or classified information. ## Description * Design, develop, and maintain LookML data models, Looks, and Looker dashboards that deliver actionable business intelligence to client program stakeholders and leadership. * Build and deploy machine learning models for classification, prediction, anomaly detection, and natural language processing use cases using Python (scikit-learn, TensorFlow, or PyTorch) and cloud AI/ML services (Vertex AI, SageMaker, or Azure ML). * Conduct exploratory data analysis, statistical modeling, and hypothesis testing to surface patterns and insights in client operational and program data. * Develop and maintain feature engineering pipelines, model training workflows, and model serving infrastructure integrated with cloud data platforms and BigQuery. * Partner with Data Engineers to define data requirements, validate pipeline outputs, and ensure analytical datasets meet quality and completeness standards. * Collaborate with program leadership and client government stakeholders to translate mission requirements into analytical problem definitions and measurable KPIs. * Implement responsible AI practices - model explainability, bias assessment, and documentation standards - consistent with federal AI governance frameworks. * Build and maintain automated reporting and alerting workflows that surface operational metrics and anomalies to the right stakeholders at the right time. * Document data science methodologies, model assumptions, validation results, and performance metrics to support ATO and audit requirements. * Mentor junior analysts and support adoption of data-driven practices across the delivery team. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Advanced Typing in TypeScript](https://www.wearedevelopers.com/videos/496-advanced-typing-in-typescript) - [Vectorize all the things! 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