Data Scientist

• Consult with internal clients and build data products and workflows to support critical operations
• Migrate and modernize clients’ workloads from legacy environments to the cloud to realize quantifiable improvements
• Spearhead AI adoption with clients to drive business outcomes
• Create reference use cases with supporting tutorials, reference code, and training to drive adoption of cloud tooling for concrete business results
• Host office hours to upskill clients
• Develop, train, and deploy machine learning solutions to solve complex business problems

Senior Data Scientist

• Support the design, calibration, and testing of predictive risk models used to evaluate mishap risk across Navy communities
• Analyze complex data to identify relationships, patterns, anomalies, and potential predictors
• Apply time series analysis, forecasting, statistical modeling, causal inference, and anomaly detection
• Perform feature engineering, cross-validation, and model performance evaluation using measures such as precision and recall
• Apply Python, R, or similar programming languages to real-world data science challenges
• Use tools and libraries such as Pandas, NumPy, Scikit-learn, SciPy, or comparable technologies
• Partner with experienced Data Scientists and Software Engineers to transition analytical models from development into operational environments
• Participate in technical exchange meetings
• Gain exposure to deployment, maintenance, and interpretation of operational AI and predictive analytics solutions

Associate Data Scientist

• Direct existing principles and guide development of new policies
• Produce innovative solutions through exploratory data analysis of complex, high-dimensional datasets
• Identify opportunities, pose business questions, and make discoveries
• Generate and test hypotheses and analyze and interpret results
• Develop and code complex software programs, algorithms, and automated processes
• Translate complex business and technical needs into technological objectives
• Document and present findings to stakeholders to support critical decision making
• Serve as a subject matter expert and advanced individual contributor
• Maintain relationships with team members, subject matter experts, and senior leaders
• Research and apply new best practices and ethical AI
• Advise senior leaders on analytical insights and solutions
• Lead complex technical projects and initiatives with significant impact
• Lead development and enhancement of practices, procedures, and instructions
• Serve as lead technical resource for team members
• Mentor and assist lower-level employees

Senior Principal Data Scientist – Marketing Data Specialist

• Research, design, and develop visualization solutions supporting investigative and audit products
• Design experiments, test hypotheses, and build scalable data science and artificial intelligence models
• Design, develop, and adapt mathematical, statistical, econometric, and analytical solutions for audits, investigations, research, and support functions
• Lead natural language processing, predictive analytics, and machine learning model development, training, evaluation, testing, refinement, deployment, and maintenance
• Translate complex technical findings into understandable narratives
• Prepare documentation including requirements, test plans, user manuals, technical diagrams, and training materials
• Develop project communications and maintain relationships with project teams, stakeholders, and management
• Advise on data access, quality, storage, and related project needs
• Contribute to and present training and conference materials
• Collect and analyze data from diverse sources to develop trends, descriptive statistics, and insights
• Research, extract, evaluate, interpret, and visualize data as actionable intelligence for auditors and investigators detecting, preventing, and responding to fraud, waste, and abuse
• Use relational databases, data lakes, and data lakehouses to create business intelligence tools, summary tables, comparison graphs, and temporal, association, and link analysis charts
• Collaborate with agencies and peers to share information and learn analytical tools and techniques
• Develop database application and environment expertise and share it with coworkers

• Extract medical and claims-relevant data using NLP and tune models with VA datasets
• Build and maintain NLP pipelines supporting automation and analytics in claims adjudication
• Collaborate with VA stakeholders to define data science requirements and deliver solutions
• Ensure quality control, model accuracy, and performance through testing and iteration
• Document data processing workflows, model design, and tuning procedures
• Contribute to integration of NLP models within VA systems and infrastructure

NLP Data Scientist

• Support the design, calibration, and testing of predictive risk models evaluating mishap risk for individual Navy communities
• Extract insights from data to make predictions, understand relationships, and identify unusual patterns using time-series/forecasting, causal inference, statistical modeling, and anomaly detection
• Support feature engineering, cross-validation, and creation of performance metrics such as precision and recall to minimize error and eliminate overfitting
• Partner with software engineers and senior data scientists to integrate features and transition analytical models into operational environments
• Participate in technical exchange meetings
• Assist in training personnel on model maintenance and interpretation
• Support the Naval Safety Command through development, testing, and deployment of predictive analytics models diagnosing and predicting precursors to Naval mishaps and safety hazards

• Design and develop data visualization and dashboard solutions using Tableau
• Lead and review data-cleaning scripts using R and Python
• Maintain and enhance dashboards, analytics solutions, and reporting tools for operational and strategic decision-making
• Balance competing priorities, including quick-turn and ad hoc requests
• Support client services, business development, internal firm initiatives, and ongoing professional development
• Support organizational and mission goals within the Department of Homeland Security
• Implement data analytics and data science solutions spanning data querying, wrangling, engineering, visualization, dashboarding, BI, and predictive analytics

Junior Data Scientist

• Oversee product development from development through operational deployment
• Guide Scrum Masters and developers through the requirements process
• Maintain and prioritize Backlogs for one or more Scrum teams in Jira
• Add backlog items as feedback is received
• Assist Scrum teams in developing user stories and acceptance criteria
• Review and accept completed work against defined acceptance criteria
• Ensure teams work on the highest-value approved priorities while avoiding scope creep
• Work with government stakeholders to advance new efforts through the requirements process
• Assist the Chief Architect and Chief Engineer with Roadmap development and future program vision
• Oversee projects to ensure successful completion and adherence to timelines
• Monitor project progress and identify potential issues with the Scrum Master
• Provide contract and government leadership visibility into team progress and impediments through CDRLs, KPIs, and other reporting
• Complete safety, quality, procedure compliance, training, and emergency-response responsibilities as applicable

Product Manager, Data Authorization

• Conduct descriptive and diagnostic analyses of workforce data to surface trends, anomalies, and actionable patterns
• Apply hypothesis testing, correlation analysis, regression techniques, and other methods to answer workforce questions
• Extract, join, transform, and validate data from enterprise data warehouses and HR systems using SQL
• Translate business questions into structured analytical approaches and deliver end-to-end analyses from scoping through presentation
• Communicate findings to HR and business stakeholders through visualizations, written summaries, and presentations
• Partner with HR functions throughout analytics initiatives, from data gathering and exploratory analysis through delivery and documentation
• Ensure the integrity, accuracy, and confidentiality of highly sensitive workforce data
• Support investigations into attrition drivers, workforce planning, internal mobility, employee engagement, and performance outcomes
• Develop increasingly sophisticated modeling and analytic solutions to provide advice for senior workforce decisions

Data Scientist – Talent Analytics, Organizational Research

• Design and build machine-learning, analytics, NLP, and generative-AI solutions using structured and unstructured data
• Develop multi-stage workflows transforming documents and free text into reliable, actionable outputs
• Build and evaluate predictive models, prioritization, classification, analytics, and decision-support workflows
• Establish rigorous approaches to data quality, experimentation, model evaluation, validation, monitoring, and human review
• Diagnose weak-performing approaches, identify root causes, and redesign or abandon solutions when evidence does not support deployment
• Design solutions considering provenance, lineage, privacy, reproducibility, data governance, and AI governance
• Collaborate with technical teams, domain experts, clients, and leadership to translate complex requirements into defensible technical solutions
• Take ownership from ambiguous problem definition through evaluation and production