Jobs at Elder Research

Manages client relationships and technology and analytics project delivery. Advises data science and engineering teams on business analysis, technology approaches, project scope, schedules, costs, risks, and quality assurance. Develops client engagement strategies, technology roadmaps, proposals, statements of work, and pricing. Partners with executives to identify portfolio growth opportunities and communicates the business value of analytics, statistics, and machine learning.

Lead development and deployment of machine learning, statistical, and graph-based algorithms on large datasets for Intelligence Community clients. Prototype and evaluate models, design experiments, generate visualizations and reports, translate results into actionable recommendations, automate analytics into production, assess client readiness, and mentor/lead a team of data scientists while staying current with emerging ML techniques.

The Data Scientist will develop and maintain ML and NLP models, enhance data products, and support federal agency decisions using analytics.

Support IRS projects by developing, validating, and deploying predictive and statistical models on large tax and financial datasets. Perform data cleaning, feature engineering, anomaly detection, and risk scoring using Python/R, SQL, and Databricks. Communicate results to stakeholders and collaborate with cross-functional teams to inform audit prioritization, fraud detection, and compliance efforts.

Perform data exploration and analysis on large structured and unstructured datasets using SQL and Python. Clean and process data, build dashboards and reports with Power BI and Tableau, consult with stakeholders to gather requirements, and communicate findings to end users. Work in a hybrid Arlington, VA environment supporting federal clients.

Design, develop, validate, and deploy statistical and machine learning models to detect fraud, anomalies, and noncompliance in large tax and financial datasets. Clean and feature-engineer data, run robustness and sensitivity tests, collaborate with stakeholders, and present technical and non-technical findings. Support end-to-end data science lifecycle and productionization in a government environment.

Develop, validate, and deploy statistical and machine learning models on large structured and unstructured tax datasets to detect fraud, prioritize audits, and score compliance risk. Clean and explore data, perform feature engineering, collaborate with stakeholders, and present technical findings to diverse audiences.

Analyze large structured, semi-structured, and unstructured datasets using SQL and Python; clean and process data; build dashboards and reports with Power BI and Tableau; consult technical and non-technical stakeholders; communicate analysis and deliverables to end users on federal government projects. Must possess IRS Public Trust clearance.

Manage and lead technical teams to deliver data and analytics projects on scope, on time, and within budget; liaise with clients and technical staff; oversee contractual, financial, and resourcing matters and facilitate analytics delivery from design through deployment.

Analyze large structured and unstructured datasets using SQL and Python, clean and process data, build dashboards in Power BI/Tableau, consult with stakeholders, and communicate findings to deliver analytic solutions for federal clients.

Lead and support full-lifecycle data science projects (forecasting, NLP, classification/regression, optimization). Design production-ready solutions within client environments, consult with stakeholders to define ambiguous problems, communicate technical findings, and develop/teach bespoke analytics training.

Analyze large structured and unstructured datasets using SQL and Python; clean and process data; build dashboards and reports with Power BI/Tableau; consult stakeholders and communicate findings to end users.

Design, build, and maintain secure, scalable data pipelines and ML data workflows to support IRS fraud detection and compliance analytics. Collaborate with data scientists and stakeholders, troubleshoot production issues, produce documentation and briefings, and operate in restricted government environments.

Develop, validate, and deploy predictive and statistical models on large tax and financial datasets to detect fraud and non-compliance. Perform data exploration, feature engineering, and model evaluation using Python/R, SQL, and Databricks. Collaborate with government clients and cross-functional teams, deliver technical and non-technical briefings, and ensure models are explainable, defensible, and maintainable in secure government environments.

Support IRS tax compliance and fraud detection by developing, validating, and deploying predictive and statistical models. Clean and analyze large datasets, apply supervised and unsupervised learning (including NLP and graph analytics), collaborate with clients and teams, and deliver technical briefings and defensible, explainable model results.

Perform data exploration and analysis on large structured and unstructured datasets using SQL and Python; build and deploy dashboards in Power BI/Tableau; consult with stakeholders, communicate findings, and collaborate with data scientists and engineers to deliver analytic solutions for federal clients.

Join a cross-functional team to explore and analyze large structured and unstructured datasets using SQL and Python, build and deploy dashboards (Power BI, Tableau), consult with stakeholders, and communicate analytic results and reports to end users for federal government clients.

Consult with stakeholders to explore and analyze large structured, semi-structured, and unstructured datasets using SQL and Python; clean, process, and manage data; build and deploy dashboards and reports (Power BI, Tableau); communicate findings to end users; collaborate with cross-functional teams to translate requirements into analytic solutions.

Work with clients and technical staff to design, develop, and deploy predictive models and data-driven analytical solutions. Perform data extraction, ingestion, and modeling; evaluate and improve models; translate business rules into technical specifications and communicate results to stakeholders.

Support IRS analytics to detect fraud and non-compliance by developing, validating, and deploying predictive and statistical models. Clean and analyze large datasets, perform feature engineering, apply supervised and unsupervised techniques (including NLP and graph analytics), collaborate with stakeholders, and deliver technical and non-technical briefings. Work across the full data science lifecycle and operate in secure government environments.