Data Scientist

• Define and articulate the product vision, strategy, and roadmap for enterprise data platforms in alignment with business goals and technological advancements.
• Lead cross-functional teams through the entire product lifecycle, from concept to launch and beyond, for data platform solutions.
• Conduct market research, competitive analysis, and stakeholder interviews to gather insights and inform product decisions related to data management.
• Prioritize features and initiatives based on stakeholder feedback, business impact, and technical feasibility, making trade-off decisions when needed.
• Drive product development efforts, including defining requirements, managing backlog, and ensuring timely delivery of high-quality data platform releases.
• Collaborate with stakeholders across the organization to ensure alignment and drive consensus on key decisions related to data management and governance.
• Continuously monitor data platform performance, analyze metrics, and iterate on features to optimize user experience and business outcomes.
• Connect with internal customers to regularly understand their data needs and build long-lasting relationships.

Senior Product Manager – Data Products

• Define and drive the multi-year product vision for Data Compass Experience and AI.
• Create and maintain a roadmap aligned to Data Compass strategic priorities.
• Own the product strategy and roadmap for Compass AI.
• Lead initiatives including intent-based discovery, multi-agent experiences, chat with metrics, personalized recommendations, ambient AI experiences, and agentic workflows.
• Drive a unified Data Compass experience across catalog, quality, lineage, classification, analytics, and future platform capabilities.
• Enable associates to move seamlessly from question to discovery, trust validation, insight, and action.
• Conduct user research and customer discovery across business and technical audiences.
• Own product requirements, prioritization, roadmap planning, and release execution.

Senior Product Manager, Data Compass Experience – AI

• Lead the design, development, and deployment of advanced analytics and AI/ML solutions for mission-critical applications
• Collaborate with multidisciplinary teams of analysts, engineers, and developers to solve complex challenges and deliver innovative, production-ready algorithms and platforms
• Apply cutting-edge techniques in statistical analysis, predictive analytics, entity resolution, graph analytics, explainable AI, and operational analytics
• Work with diverse data types and leverage modern tools such as Python, PyTorch, Scikit-learn, LLM frameworks, and geospatial analytics platforms
• Contribute to the integration of AI, DevSecOps, data engineering, platform engineering, cybersecurity, and observability in a fast-paced, engineering-centric environment

Senior Data Scientist

• Responsible for mining big data, interpreting and analyzing complex data sets
• Develops and deploys predictive models to analyze company performance and improve customer experiences
• Applies statistical techniques and machine learning algorithms to identify trends within Mazda data
• Collaborates closely with data engineers, analysts, and business stakeholders to integrate data-driven solutions

• Drive the development of innovative AI based solutions for enterprise stakeholders
• Translate business needs into AI solutions that align with strategic goals
• Design and build best-in-class AI and agent evaluation capabilities
• Deliver the analytical solution to complex business problems
• Document objectives, assumptions and processes

Senior Data Scientist – AI Services, Platforms

• Architect and deliver enterprise AI/ML solutions
• Lead strategic initiatives and mentorship
• Collaborate with product and engineering teams

• Design and develop enterprise-grade Generative AI applications using state-of-the-art Large Language Models.
• Architect scalable Retrieval-Augmented Generation (RAG) systems for enterprise knowledge retrieval.
• Develop AI assistants, copilots, chatbots, document intelligence solutions, and autonomous AI agents.
• Build domain-specific NLP solutions for document processing, search, summarization, classification, information extraction, and question answering.
• Work extensively with open-source and commercial LLMs including GPT, Llama, Mistral, Qwen, Claude, Gemini, DeepSeek, and similar foundation models.
• Select appropriate model architectures based on enterprise use cases
• Work on the latest applications of data science to solve business problems
• Work directly with client stakeholders to translate business problems into high level analytics solution designs
• Present analytic solutions to business audiences highlighting robustness of the solution and how it could help generate business value

Senior Data Scientist – GenAI, NLP

• Perform/utilize statistics, machine learning and analytic approaches to answer key intelligence questions, producing results and re-usable products that provide real value to Analysts
• Apply machine learning techniques to identify and transform data features, find hidden patterns and trends, build and optimize classifiers, create automated anomaly detection systems, and automate steps of a process
• Evaluate statistical models to determine the validity of analyses, implement evaluated models into production by collaborating with software developers, periodically re-evaluate and refine machine learning models being used in production
• Curate and collect the data from a variety of traditional and non-traditional sources: extract data from sources, transform and integrate data in line with existing data, and load data into data stores for access by others
• Collaborate with Data Scientists to develop processes and tools to monitor and analyze model performance and data accuracy
• Work with analysts to interpret analytic results and refine analysis as needed
• Effectively communicate results and ideas to key decision makers, analysts and other stakeholders and shall provide information as appropriate
• Perform documentation of all processes, models and activities by developing, documents, and implement a configuration management plan for data sets
• Research latest data science tradecraft and technology

Data Scientist – AI/Machine Learning

• Serve as a technical lead on AI and machine learning initiatives, providing guidance on solution architecture, model selection, implementation approaches, and technical best practices.
• Mentor and support junior and mid-level data scientists through code reviews, knowledge sharing, technical coaching, and collaborative problem solving.
• Establish and promote best practices for MLOps, model evaluation, model monitoring, reproducibility, and responsible AI development
• Build and deploy end-to-end ML pipelines on AWS (e.g., SageMaker, S3, Glue) for scalable training, evaluation, and inference.
• Develop and implement advanced NLP solutions, including text classification, entity recognition, topic modeling, and semantic search using models such as BERT and transformer-based architectures.
• Design, build, and productionize RAG (Retrieval-Augmented Generation) systems, including document ingestion, embedding pipelines, vector search, and LLM orchestration.
• Develop LLM-powered applications, including prompt engineering, evaluation frameworks, and optimization techniques for accuracy, consistency, and cost.
• Contribute to agentic AI system design, including multi-step reasoning workflows, tool use, and orchestration of LLM-driven agents for complex tasks.
• Implement predictive analytics and statistical modeling to uncover patterns, trends, and insights from healthcare data.
• Evaluate emerging AI technologies, frameworks, and techniques and recommend their appropriate application to government healthcare use cases.
• Perform data mining and exploratory data analysis (EDA) using state-of-the-art techniques across structured and unstructured datasets.
• Contribute to technical leadership across multiple AI initiatives while remaining an active hands-on developer and model builder.
• Build data visualizations, dashboards, and analytical tools to communicate findings clearly to technical and non-technical stakeholders.
• Evaluate model performance using appropriate metrics (e.g., accuracy, AUC, precision/recall) and present results in a clear, actionable manner.
• Collaborate in an Agile environment with cross-functional teams including engineers, analysts, and stakeholders.
• Recommend data-driven solutions and AI strategies aligned with CMS business needs and healthcare policy objectives.

• Develops explainable and high-performance reinforcement learning (RL) agents, including graph neural network-based approaches.
• Designs advanced AI patterns, such as Large Language Model (LLM) and Retrieval-Augmented Generation (RAG) systems, to enable natural language control of complex software and simulation interfaces.
• Develops and integrates AI/ML applications within DoD Modeling & Simulation environments (e.g., JLVC, JTLS-GO) to enhance realism and analytical capability.

Data Scientist III, SME

• Advise clients on end-to-end solutions across data strategy, data management, and data quality.
• Support business development, methodology development, team leadership, and delivery execution for data governance assessments and implementations.
• Design and develop data governance technology solutions across data quality, data dictionaries, business glossaries, data standards, and data policies.
• Define organizational design, governance processes, policies, roles, responsibilities, success metrics, and operating models for client data programs.
• Build roadmaps covering technology, culture, governance, processes, skills, competencies, data quality, analytics, and data management maturity.
• Lead and collaborate with data governance teams to create business cases, resource plans, implementation roadmaps, and enterprise data system assessments.
• Assess current-state environments, identify client pain points and requirements, and help define a practical vision and strategy for becoming a data-driven organization.
• Advise clients as a trusted partner and provide thought leadership on data governance, data management, cloud transformation, AI readiness, and related best practices.
• Manage resources, budgets, project delivery, team development, training, mentoring, and performance assessment.

Data Strategy and Governance Manager

• Building, enhancing, and sustaining Army applications for various mission stakeholders
• Integrating AI-enabled analytics and Army Vantage capabilities into applications and workflows
• Conducting verification and validation testing and managing a ticketing system to resolve user issues
• Performing advanced data mining to aggregate, transform, and analyze large datasets
• Carrying out data preprocessing to prepare datasets for analysis or integration
• Developing, updating, and maintaining Army 365 SharePoint sites, lists, and document libraries
• Managing user permissions across SharePoint, Qlik, and Power Apps
• Maintaining and updating template files that capture key data elements across 18 core capability areas
• Refining portfolio definitions, data dictionaries, and glossaries to ensure consistent terminology and structure

Data Scientist, 365 Developer

• Design, develop, and maintain machine learning models
• Build and deploy ML pipelines on AWS
• Develop advanced NLP solutions
• Design and productionize RAG systems
• Develop LLM-powered applications
• Implement predictive analytics and statistical modeling
• Perform data mining and exploratory data analysis
• Build data visualizations and dashboards
• Evaluate model performance and present results
• Collaborate in an Agile environment

• designs, builds, and scales an organization's foundational data infrastructure
• experience designing and building Data Lakes, Data Warehouses, and scalable data platforms in the cloud
• supports technical activities across the contract
• drives continuous improvement and innovation into program operations
• advises on technology alternatives related to processing, data storage, data access, application development, and enterprise architecture decisions
• establishes coding best practices and aligns complex data architectures with overarching business goals
• uses APIs to push and pull data from various data systems and platforms
• builds and optimizes ETL/ELT pipelines using glue and python
• packages, curates, and versions datasets for LM fine-tuning and model training jobs on Bedrock and Sagemaker
• enforces CUI handling requirements, automates PII detection, and maintains audit trails (e.g. Amazon Macie)

Data Science Advisor

• Develop capabilities to shift from the current manual system security evaluation and authorization process to a new model that emphasizes automation, streamlined processes and approvals, continuous monitoring and assessment, and network data gathering across the entire life cycle of a project.
• Leverage Python as a primary language to process data to accurately determine if resources and systems are secure
• Look for outliers to help track the progress of systems through the Risk Management Framework lifecycle.
• Identify which System a Resource belongs to determined by various attributes of the identified lost Resource against known potential System information.
• Design, develop, and maintain ETL pipelines to extract security and compliance data from multiple sources (network sensors, security tools, compliance databases), transform the data for analysis and reporting, and load it into target data repositories to support continuous monitoring and automated assessments.
• Support data engineering operations including data quality validation, pipeline monitoring, and optimization of data workflows to ensure reliable, scalable, and timely delivery of security-related data for Risk Management Framework automation and decision-making.

• Support ongoing and future programs to advance the state of the art in research and advanced machine learning, natural language processing, and data fusion applications in the areas of mission-focused big data analytics
• Work closely with a tight-knit team of data scientists and a larger team of software developers, network engineers, senior investigators, program managers, researchers, and data analysts to design, build, and optimize a Data Science platform
• Analyze a variety of big data covering national security, cyber security, business intelligence, online social media, human behavior and more
• Support multiple simultaneous projects and take open-ended or high-level guidance, independently and collaboratively make discoveries that are mission-relevant
• Bring intellectual curiosity, quantitative acumen, and customer-focus to identify novel sources of data
• Improve the performance of predictive algorithms and encourage user adoption of data analytics platforms

Data Scientist – TS/SCI

• Own the data science and applied AI roadmap for operations—agentic systems, forecasting, lead scoring, voice of the customer aggregation, and decision-support that improve throughput, reliability, and unit economics.
• Build agents and AI workflows that don't just predict but act.
• Own the data science and AI behind post-sales product experiences, including the support agent, onboarding intelligence, and customer success automation—from design through production deployment, evaluation, and quality monitoring.
• Lead, hire, and develop a data science team executing on operational and product-facing work; set standards for technical rigor, evaluation, and production quality.
• Partner with operations, finance, and product leadership to identify high-leverage problems, frame them, and translate them into operational decisions and shipped AI capabilities.
• Drive the full lifecycle from problem definition through deployment and monitoring, ensuring systems hold up in production—whether powering an internal forecast, an autonomous workflow, or a live customer interaction.
• Establish metrics and evaluation frameworks connecting this work to operational, financial, and customer outcomes (e.g., deflection, resolution quality, time-to-value, retention), including rigorous evaluation of non-deterministic AI systems.
• Collaborate with data engineering, machine learning engineering, platform, and product teams on the infrastructure, data quality, orchestration, tooling, and guardrails these systems depend on.
• Communicate findings and recommendations to executive stakeholders, balancing technical depth with business clarity.
• Champion an AI/agent-first way of working within the team—both as a hands-on technical leader (e.g., Claude Code) and by inventing agentic systems that make the team faster.

Director, Data Science

• Lead efforts to extract insights from operational, service, and performance data to identify opportunities for improvement.
• Lead development and deployment of advanced statistical models, machine learning algorithms, and predictive analytics solutions.
• Design and develop predictive models and data-driven analytical frameworks that optimize processes and support informed decision-making.
• Build models that forecast future demands, highlight operational and service-related risks, and detect performance anomalies in real time.
• Collaborate with engineering and functional teams to ensure analytical outputs are accurate, actionable, and aligned with mission objectives.
• Design experiments, feature engineering strategies, and model validation frameworks to support enterprise analytics objectives.
• Collaborate with data engineering teams to ensure scalable data pipelines supporting model training and inference.
• Integrate models into DevSecOps pipelines for automated testing, validation, and production deployment.
• Develop and maintain documentation, evaluation metrics, and model performance dashboards.
• Ensure responsible AI practices including bias detection, explainability, and performance monitoring.
• Participate in PI Planning, backlog refinement, sprint reviews, and Inspect & Adapt events to align analytics priorities with Program Increment (PI) objectives.
• Translate complex analytical findings into actionable insights for technical and executive stakeholders.
• Establish modeling standards, peer review processes, and analytical quality governance frameworks.
• Foster a collaborative, innovative, and mission-focused analytics culture within the organization.

• Lead the design, development, and deployment of advanced analytics and AI/ML solutions for mission-critical applications
• Collaborate with multidisciplinary teams of analysts, engineers, and developers to solve complex challenges and deliver innovative, production-ready algorithms and platforms
• Apply cutting-edge techniques in statistical analysis, predictive analytics, entity resolution, graph analytics, explainable AI, and operational analytics
• Work with diverse data types (structured, unstructured, open source, digital media) and leverage modern tools such as Python, PyTorch, Scikit-learn, LLM frameworks, and geospatial analytics platforms
• Contribute to the integration of AI, DevSecOps, data engineering, platform engineering, cybersecurity, and observability in a fast-paced, engineering-centric environment

• Support complex data exploration and analytics projects for Department of War clients
• Use analytical skills and data science knowledge to create real-world impact
• Share skills in data engineering and data science modeling
• Develop solutions to drive the mission forward
• Work with a multi-disciplinary team of analysts, data engineers, developers, data consumers, and mission experts
• Assess, design, develop, and maintain scalable platforms for clients
• Improve government efficiency or provide better services to the public

Data Scientist jobs in Maryland

See all jobs on JobTailor

Senior Product Manager – Data Products

Senior Product Manager, Data Compass Experience – AI

Senior Data Scientist

Data Scientist

Senior Data Scientist – AI Services, Platforms

Senior Data Scientist

Senior Data Scientist – GenAI, NLP

Data Scientist – AI/Machine Learning

Senior Data Scientist

Data Scientist III, SME

Data Strategy and Governance Manager

Data Scientist, 365 Developer

Data Scientist

Data Science Advisor

Senior Data Scientist

Data Scientist – TS/SCI

Director, Data Science

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist