Data Scientist (Looker / AI / BI)

Opportunity Overview Northramp is seeking a Data Scientist to join the team supporting client's Cloud program — a mission-critical effort to consolidate, modernize, and operate client's enterprise cloud services across IaaS, PaaS, and SaaS environments under FedRAMP High authorization. You will develop analytical models, business intelligence solutions, and AI/ML capabilities that help client derive actionable insight from its enterprise data. The role spans statistical analysis, machine learning, and data visualization — with Looker as the primary BI delivery platform — in support of program operations, resource planning, and mission-critical decision-making. This role is part of Northramp’s integrated delivery model, where engineers and advisors work as one team to bring sound judgment, disciplined execution, and deep federal experience to high-stakes modernization programs. Location & Work Arrangement Hybrid, based in the Washington, DC metro area. On-site presence at designated client locations is expected on a cadence aligned to program needs. Remote work is supported around mission and security requirements. This role is not open to candidates outside the DC region. The Ideal Candidate 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. Key Responsibilities 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.