Job Description

Job Description

Job Description

Salary:

EnDyna, Inc., a woman-owned small business (WOSB) headquartered in McLean, Virginia, is seeking talented professionals to join our team in support of a contract with the U.S. Environmental Protection Agencys (EPA). This position will directly contribute to OARs A-123 internal control and audit support initiatives, ensuring compliance, risk management, and program effectiveness across EPAs critical grant oversight activities.

Position Overview:

The Statistician/Economist/Data Scientist (SDS) is responsible for applying advanced statistical, econometric, and data science methods to support OARs grant oversight and risk management mission. With a strong academic background and substantial applied experience, this role provides rigorous analysis of large and complex datasets to detect trends, measure program outcomes, and flag anomalies that could indicate control weaknesses or fraud. By combining expertise in statistics, economics, and modern data science tools, the Data Scientist equips OAR leadership with evidence-based insights that strengthen decision-making and compliance.

Key Responsibilities:

Designs and implements quantitative models to assess grant performance, financial health, and compliance risks. This includes econometric analyses of funding distributions, statistical tests of program outcomes, and predictive models to identify grants most at risk of fraud or mismanagement. Produces dashboards and data visualizations that make technical findings accessible to OAR managers and auditors.

• Risk Mitigation: Develops analytic tools that integrate with OARs internal control framework to proactively flag high-risk transactions, unusual financial activity, or performance anomalies. For example, they may build algorithms to detect outliers in disbursement patterns or identify correlations between program characteristics and compliance findings. These insights enable management to focus resources on the highest-risk areas, aligning with OMB Circular A-123s emphasis on data-driven risk assessment.

• Audit Readiness: Ensures data used in oversight and evaluation is well-documented, reproducible, and audit-ready. The Data Scientist maintains transparent coding practices, statistical documentation, and validation protocols so that results can withstand scrutiny from GAO, OIG, or other external reviewers. By adhering to federal standards for statistical quality and transparency, this role reinforces the credibility of OARs oversight processes.
  

• Program Improvement: Provides OAR leadership with quantitative evidence to guide continuous improvement in grant administration. For example, regression analyses may reveal which grant characteristics are most strongly associated with delays in closeout, or time-series modeling may show trends in fraud indicators. By translating such findings into actionable recommendations, the Data Scientist helps shape policy updates, training, and process improvements that enhance the effectiveness of OARs programs over time.

Qualifications:

• Bachelors degree in Data Science, Statistics, Econometrics, Computer Science, or a related field (Masters degree preferred).

• 8 years of experience in data analysis, with a focus on ETL processes and data visualization.

• Proficiency with data analysis and data visualization tools.

• Experience with project management and collaboration tools.

• Strong understanding of data quality management and the ability to identify, troubleshoot, and resolve data-related issues.

• Excellent communication skills, with the ability to present data insights clearly to non-technical stakeholders.

• Attention to detail and strong problem-solving skills.

• Familiarity with cloud data platforms (AWS, Azure, Google Cloud) is a plus.

The salary will be commensurate with qualifications and experience.

It is EnDynas policy to promote equal employment opportunities. All qualified applicants will receive consideration for employment without regard to sex, race, color, ethnicity, age, national origin, citizenship, religion, physical or mental disability, medical condition, genetic information, pregnancy, family structure, marital status, ancestry, domestic partner status, sexual orientation, gender identity or expression, veteran or military status, or any other basis.

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