Data Scientist (AI/BI/Looker)

• Design, develop, and maintain LookML data models, Looks, and LookML 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.

Required Qualifications  • 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) as well as advanced SQL for complex data transformation, analytical querying, optimization, and large-scale data analysis.  • Hands-on expertise with Looker and LookML, including designing and maintaining scalable semantic models; developing complex Explores, Views, dimensions, measures, joins, and relationships; implementing derived tables and Persistent Derived Tables (PDTs); creating reusable LookML patterns; and applying strong LookML development, testing, documentation, and version-control practices. • Understanding data visualization and dashboard design best practices, including effective visual storytelling, information hierarchy, KPI design, accessibility, usability, and selecting appropriate visualizations to communicate analytical findings clearly. • Deep analytical, troubleshooting, and problem-solving skills, with demonstrated ability to perform root-cause analysis across BI, data, SQL, LookML, BigQuery, and machine learning workflows and to resolve complex technical and data-quality issues efficiently.  • Experience developing, training, validating, tuning, and deploying machine learning models using Vertex AI, including supervised learning techniques such as regression and classification and, where applicable, time-series forecasting, clustering, or other advanced analytical approaches (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.  Desired Qualifications  • Google Cloud Profes

• Health Care Plan (Medical, Dental & Vision) • Retirement Plan (401k, IRA) • Life Insurance (Basic, Voluntary & AD&D) • Paid Time Off (Vacation, Sick & Public Holidays) • Family Leave (Maternity, Paternity) • Short Term & Long Term Disability • Training & Development • Work From Home • Wellness Resources • Employee Bonus Programs

Opportunity Overview  Northramp is seeking a Data Scientist to join the team supporting client's Cloud Modernization 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 our client derive actionable insights from its enterprise data. The role spans statistical analysis, machine learning, and data visualization — with BigQuery and 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  Remote or 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 act on. You know when to reach for a simple statistical model and when the complexity of ML is 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 LookML 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. Required Qualifications  • 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) as well as advanced SQL for complex data transformation, analytical querying, optimization, and large-scale data analysis.  • Hands-on expertise with Looker and LookML, including designing and maintaining scalable semantic models; developing complex Explores, Views, dimensions, measures, joins, and relationships; implementing derived tables and Persistent Derived Tables (PDTs); creating reusable LookML patterns; and applying strong LookML development, testing, documentation, and version-control practices. • Understanding data visualization and dashboard design best practices, including effective visual storytelling, information hierarchy, KPI design, accessibility, usability, and selecting appropriate visualizations to communicate analytical findings clearly. • Deep analytical, troubleshooting, and problem-solving skills, with demonstrated ability to perform root-cause analysis across BI, data, SQL, LookML, BigQuery, and machine learning workflows and to resolve complex technical and data-quality issues efficiently.  • Experience developing, training, validating, tuning, and deploying machine learning models using Vertex AI, including supervised learning techniques such as regression and classification and, where applicable, time-series forecasting, clustering, or other advanced analytical approaches (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.  Desired Qualifications  • Google Cloud Professional Machine Learning Engineer or equivalent AWS/Azure ML certification.  • Demonstrated advanced LookML experience.  • Security+ or equivalent certification.  • Experience with NLP, computer v