Data Scientist

You have strong proficiency in Python and SQL, experience working with structured and unstructured datasets, and the ability to communicate technical findings clearly to non-technical stakeholders. You thrive in environments where critical thinking, innovation, and attention to detail are essential.

You will deliver advanced data analytics and modeling solutions that strengthen the National Science Foundation Office of Inspector General’s oversight, audit, investigative, and operational capabilities. By transforming complex, raw data into reliable and actionable intelligence, you will help investigators, auditors, and leadership identify risks, detect anomalies, and make evidence-based decisions. You will develop predictive models, risk assessments, dashboards, reports, and scalable analytical solutions using statistical, machine-learning, and artificial-intelligence methodologies. You will also translate technical findings into clear, defensible recommendations and maintain well documented, reproducible analytical processes that support accuracy and continuity of operations.

• Perform data analytics, statistical and non-statistical modeling, data mining, and data-management activities supporting projects and initiatives.
• Gather and store source data in its original form, then process, clean, normalize, validate, and integrate structured and unstructured data from multiple sources.
• Design, develop, and maintain analytical models, scripts, algorithms, and automated workflows.
• Design experiments, test hypotheses, and develop scalable analytical models using data-science and artificial-intelligence methods, including machine learning.
• Design, develop, and adapt mathematical, statistical, econometric, and other analytical solutions supporting audit, investigative, research, and program evaluation activities.
• Develop interactive dashboards and reporting tools using Power BI, Tableau, or similar platforms.
• Conduct risk modeling, anomaly detection, trend analysis, and predictive analytics to support investigations, audits, and inspections.
• Collaborate with investigators, auditors, analysts, and subject-matter experts to define analytical requirements and deliver data-driven solutions. 
• Use Python, SQL, and other programming languages to manipulate, analyze, and transform datasets and automate analytical processes.
• Perform ad hoc audit and investigative data-analysis requests and communicate findings in written and verbal formats.
• Prepare comprehensive reports addressing data adequacy and quality, methodologies, assumptions, results, findings, recommendations, and the relevance of the issues under review.
• Document data sources, methodologies, model assumptions, analytical workflows, code, data pipelines, and models to ensure transparency, reproducibility, and continuity. 
• Provide training to staff on all work products developed, including preparing user guides, manuals, technical documentation, and other knowledge-transfer materials.
• Monitor, maintain, and update analytical models, scripts, and data workflows as technologies, data sources, and mission requirements evolve.
• Ensure compliance with applicable federal security, privacy, accessibility, and data-governance requirements.

• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, Information Systems, or a related field.
• Minimum of four (4) or more years of professional experience in data science, analytics, statistical modeling, or a related technical discipline.
• Strong proficiency in Python and SQL.
• Extensive knowledge of data collection, extraction, cleaning, transformation, normalization, validation, and integration across multiple data sources.
• Extensive knowledge of statistical analysis and modeling, including predictive modeling, risk modeling, machine learning, and anomaly-detection techniques.
• A proven track record of deploying predictive or prescriptive models used to drive operational improvements or inform strategic decision-making.
• Experience working with both structured and unstructured datasets.
• Experience developing dashboards and visualizations using Power BI, Tableau, or similar tools.
• Ability to design interactive dashboards that allow users to drill down into specific metrics without compromising performance.
• Familiarity with federal data governance, security, and privacy requirements.
• Strong written and verbal communication skills, including the ability to present technical findings clearly to non-technical audiences.
• Ability to work independently and manage multiple priorities in a federal support environment.
• Must be a U.S. citizen and successfully complete the required background investigation and onboarding process.

• Competitive compensation package
• Comprehensive medical, dental, and vision coverage
• Company-sponsored retirement plans with matching contributions
• Professional development and continued learning opportunities
• Additional perks and discounts available to employees

The above job description is intended to describe the general nature and level of work being performed by individuals assigned to this position. It is not intended to be an exhaustive list of all responsibilities, duties, and skills required. Candidates possessing the necessary qualifications for the position will be considered.

Lawelawe Technology Services is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status, and will not be discriminated against on the basis of disability.

Offers of employment are contingent upon satisfactory completion of a comprehensive background verification, inclusive of a criminal record check. Employment may be subject to other background checks, as required by the position.

We are committed to fair and equitable compensation practices and are transparent about our pay structures. Our pay transparency efforts are aligned with state laws and regulations to ensure compliance and promote pay equity.

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