Jobs at Elder Research

The Data Engineer will develop secure, scalable data pipelines for IRS applications, supporting complex analytics and machine learning to combat fraud and ensure compliance. Responsibilities include pipeline engineering, troubleshooting, and collaboration with data teams to create production-ready analytics solutions.

The Data Scientist will analyze tax data, develop predictive models, and support IRS initiatives to improve compliance, fraud detection, and risk assessment in a hybrid work environment.

The Project Manager will oversee projects, manage technical teams, ensure project delivery on scope and time, and maintain client satisfaction.

As a Data Analyst, you will explore and manage large datasets, build visual dashboards, and communicate insights to stakeholders. Responsibilities include collaborating with teams, cleaning data, and applying analytical skills to address complex issues.

The Fraud Analytics SME analyzes fraud detection patterns, guides teams in detecting fraud schemes, validates analytical outputs, and supports operational reviews and discussions.

The Senior Data Engineer will design and maintain data pipelines and infrastructure for fraud detection analytics, ensuring data integrity and supporting testing across platforms.

Drive advanced modeling and analytics for fraud detection and identity theft. Lead technical initiatives and manage full model lifecycle.

The Principal Analytics Manager leads analytics initiatives focused on fraud detection, manages multidisciplinary teams, and coordinates with stakeholders to deliver actionable insights on time.

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.