Data Scientist

• Lead and grow the data science team, setting objectives, managing performance, and developing team members
• Hire the next data scientists and own the hiring process end to end
• Build the data collection foundation for future compliance systems
• Own model governance, including inventory, tiering, validation, testing evidence, drift monitoring, threshold breaches, reviews, and remediation
• Lead Elliptic’s data science work by framing research questions, running experiments, and making recommendations
• Write code, review methodology, and make important technical decisions
• Own existing work on clustering, attribution, heuristics, and labelling
• Partner with Intelligence Collection, Collection Engineering, Research and Investigations, the Chief Scientist, Product, and Engineering
• Set standards for AI use, verification, and team workflows
• Deliver a scalable collection plan, compliance-system recommendations, a data science hire, governance in good standing, agreed objectives, improved output reliability or throughput, and technical credibility within the first six months

Data Science Lead

• Design and implement ML/DL pipelines for microscopy image analysis
• Preprocess and clean large-scale microscopy datasets
• Develop, optimize, and fine-tune classical and deep learning models for segmentation, feature extraction, and classification
• Integrate and scale image analysis protocols into high-throughput computational pipelines
• Participate in code reviews and contribute to efficient, maintainable, well-documented codebases
• Maintain reproducible analysis records, version-controlled code, documented parameters, and traceable results
• Coordinate with experimental scientists on data collection and study design
• Track developments in machine learning and image analysis and evaluate promising methods
• Work with large-scale microscopy datasets on dedicated HPC computing infrastructure
• Collaborate with multidisciplinary computational and experimental research teams

Data Scientist II, Deep Learning, Image Analysis

• Build scalable end-to-end data science solutions for Walmart Marketplace data products
• Own the MLOps lifecycle, including data monitoring, code refactoring, and model monitoring workflows
• Develop and maintain scalable MLOps infrastructure, including Kafka pipelines for unified logging and monitoring
• Apply SRE principles to ML workloads, optimize cloud deployments, monitor performance, and troubleshoot latency or operational issues
• Lead code quality and engineering best practices through code reviews and mentoring junior MLEs
• Provide high-level architectural guidance, break down complex tasks, and resolve project challenges
• Build continuous, distributed, and scalable training, inference, and performance-monitoring pipelines
• Enhance data feedback and annotation workflows for labeling teams
• Consult with product and business stakeholders to build, scale, and deploy machine learning solutions
• Collaborate cross-functionally to align AI solutions with Walmart’s business objectives
• Build and deploy end-to-end models while balancing accuracy, computational efficiency, and business impact

Staff Data Scientist

• Maintain CSET’s data infrastructure
• Extract, classify, cluster, annotate, and resolve entities in data
• Produce rigorous policy research and high-quality data resources
• Improve bibliometric data and develop methods and metrics to identify emerging science and technology areas
• Provide open data and infrastructure supporting research and decision-making
• Improve CSET’s Map of Science and related tools
• Build and maintain data pipelines and processing techniques for large datasets using Airflow
• Design, evaluate, and implement AI-enabled solutions and advanced modeling
• Ingest structured and unstructured datasets into Google Cloud Platform
• Document and communicate CSET methods and data resources to internal and external audiences
• Collaboratively develop research designs and identify appropriate data and methods
• Interpret results and draw valid inferences to support research and publications
• Communicate findings through visualizations, written outputs, web interfaces, and presentations
• Monitor trends in AI, machine learning, biotechnology, and national security policy
• Contribute to internal working groups, seminars, and discussions
• Support and mentor colleagues
• Uphold CSET’s mission, values, and culture
• Perform additional duties as assigned

Data Scientist, Security and Emerging Technology

• Lead the design, development, and deployment of advanced analytics and machine learning solutions
• Partner with clients and stakeholders to understand business objectives and translate requirements into analytical approaches
• Analyze large, complex datasets to uncover insights, identify opportunities, and support strategic decision-making
• Develop and validate statistical, predictive, and machine learning models
• Communicate technical findings and recommendations to executive and non-technical audiences
• Provide technical leadership and mentorship to data scientists, analysts, and cross-functional project teams
• Collaborate with data engineering, product, and business stakeholders to support end-to-end solution delivery
• Establish best practices for model development, testing, validation, documentation, and performance monitoring
• Contribute to project planning, solution architecture, estimation, and delivery execution
• Support business development through technical expertise, solution ideation, and client presentations

Lead Data Scientist

• Support Bungie's product security initiatives and reduce the impact of bad actors in Bungie games
• Work with organizational partners to gather requirements, design project plans, determine approaches, and define success criteria for machine learning solutions
• Design, develop, deploy, and maintain end-to-end machine learning solutions in a cloud environment
• Implement and maintain model evaluation, monitoring, and observability
• Build integrations for machine learning models into game development pipelines
• Transform raw data and build efficient data pipelines for modeling and analytical capabilities
• Communicate analysis results to technical and non-technical colleagues
• Own solution implementation and evaluation end-to-end

Senior Machine Learning Data Scientist

• Design and deploy production-scale AI/ML solutions across risk intelligence, investigations, document intelligence, anomaly detection, entity resolution, graph analytics, forecasting, optimization, and agentic AI
• Build end-to-end capabilities spanning data preparation, modeling, evaluation, deployment, monitoring, and continuous improvement
• Partner with Engineering and Product on architecture, reusable AI services, and build-vs-buy decisions
• Establish strong evaluation and Responsible AI practices
• Mentor other data scientists
• Contribute to technical standards and platform strategy across Global Governance
• Translate high-value governance and risk problems into scalable AI solutions
• Develop reusable patterns that improve speed, quality, and measurable business outcomes

Principal Data Scientist

• Define AI/ML strategy across Global Governance
• Lead development of production-scale AI solutions for risk intelligence, investigations, anomaly detection, computer vision, graph analytics, optimization, and agentic AI
• Architect reusable AI platforms and patterns
• Establish evaluation and Responsible AI standards
• Influence build-vs-buy and long-term technology decisions
• Partner with Business, Product, Engineering, and Data Science from problem framing through deployment and measurable outcomes
• Mentor senior scientists and engineers
• Drive best practices in experimentation, model validation, MLOps, observability, explainability, and enterprise AI governance
• Shape Walmart’s AI/ML vision for Global Governance across security, compliance, privacy, legal, product safety, trade compliance, and related domains

Data Scientist jobs in Washington