Data Science Specialist

Stride, Inc.•US - VA - Remote, VA

5d•$70,202 - $120,966•Remote

About The Position

The Data Science Specialist, Audit & Compliance Analytics supports Compliance, Funding Compliance, Internal Audit, and SOX by applying data analytics to audit, testing, monitoring, and risk management activities. The role combines audit and internal control knowledge with technical data skills to improve the efficiency, consistency, and depth of assurance activities across the organization. The specialist analyzes large and complex datasets, develops repeatable testing routines, identifies exceptions and potential risks, and creates audit-ready documentation and reporting. The role also helps expand the use of automation, AI, and modern analytics tools across Audit, Risk, and Compliance. The position supports audit, SOX, compliance, privacy monitoring, and funding compliance activities; develops SQL- and Python-based analytics and automated testing; and collaborates with Internal Audit, Compliance, Funding, IT, Data Engineering, GRC, and business stakeholders. The position has no formal supervisory responsibilities and is virtual for residents of the 50 states and D.C.

Requirements

Bachelor's degree in Accounting, Finance, Data Analytics, Information Systems, Computer Science, Business, or a related field.
Five years of experience in external audit, Internal Audit, SOX, risk advisory, compliance testing, or another assurance function.
Demonstrated understanding of internal controls, audit methodology, control testing, evidence evaluation, and audit documentation.
Experience using data analytics to support audit, compliance, risk, SOX, or control testing.
Strong SQL and Python skills and experience querying and analyzing large or complex datasets.
Strong analytical and problem-solving skills, including the ability to identify exceptions, trends, inconsistencies, and potential control issues.
Ability to translate audit or compliance requirements into data queries, testing procedures, and analytical routines.
Strong attention to detail and commitment to data accuracy.
Ability to clearly document methodology, assumptions, testing procedures, results, and supporting evidence.
Ability to manage multiple priorities and meet deadlines.
Effective written and verbal communication skills.
Ability to work collaboratively with technical and non-technical stakeholders.
Proficiency with Microsoft Office applications, including Outlook, Word, Excel, PowerPoint, Project, and Visio, and web proficiency.
Ability to clear the required background check.

Nice To Haves

Experience at a Big 4 accounting or professional services firm in Audit, Risk Advisory, Technology Risk, SOX, Data & Analytics, or a related practice.
Experience performing SOX, ITGC, operational, financial, compliance, or technology-related testing.
Experience using analytics for population-based testing or to identify exceptions across large datasets.
Experience with Power BI, Tableau, or other data visualization tools.
Experience with SQL and Python or other scripting languages for data analysis and automation.
Experience with Snowflake, DBT, and GitHub.
Experience working with enterprise systems such as ERP, HRIS, SIS, LMS, CRM, or financial systems.
Familiarity with data governance, data quality, data lineage, access management, or privacy concepts.
Experience developing automated audit or compliance testing.
Familiarity with AI-enabled analytics or emerging technologies.
Experience in an education, government, regulated, or highly controlled environment.

Responsibilities

Apply data analytics to support Internal Audit, Compliance, SOX, operational reviews, and other assurance activities.
Translate audit and compliance objectives into data requirements, testing procedures, queries, and analytical routines.
Develop and execute data-driven testing procedures to evaluate transactions, populations, processes, and controls against defined requirements.
Analyze complete populations to identify trends, anomalies, exceptions, and potential control issues.
Perform data validation, reconciliation, and completeness and accuracy procedures.
Evaluate testing results and supporting evidence and document conclusions and exceptions.
Develop repeatable analytics for recurring testing and monitoring, and identify opportunities to replace manual or sample-based testing with automated or population-based analytics.
Escalate significant exceptions, anomalies, and data quality concerns appropriately.
Support Internal Audit and SOX engagements through data analysis, population development, control testing, and exception analysis.
Prepare and validate populations used for audit and control testing; test key reports, system-generated data, and other information used in controls.
Perform data-driven procedures to assess completeness, accuracy, validity, and consistency, and support testing of key controls and management review controls.
Develop automated testing routines for recurring SOX and audit procedures.
Prepare audit-ready workpapers and documentation covering data sources, queries, filters, methodology, testing steps, and results.
Support Internal Audit and SOX teams in increasing testing coverage and improving testing efficiency.
Support recurring compliance monitoring through data analysis, exception reporting, and automated testing.
Analyze access, user, and other privacy-related datasets in support of FERPA and applicable state requirements.
Develop and maintain monitoring routines to identify unusual activity, exceptions, or potential compliance issues.
Test data against policies, procedures, regulatory requirements, and established controls; document procedures, results, exceptions, and evidence.
Partner with Compliance and other stakeholders to investigate and resolve data-related questions and exceptions.
Perform analytics supporting the accuracy and completeness of district and state funding submissions.
Validate enrollment, attendance, demographic, and program participation data; analyze funding-related populations for anomalies, inconsistencies, and potential reporting issues.
Investigate data exceptions and discrepancies and support their resolution with business and data teams.
Develop repeatable analytics and automated reports to strengthen funding compliance monitoring and maintain supporting documentation and evidence.
Write and maintain SQL queries and Python to extract, transform, validate, and analyze data from multiple sources.
Develop reusable datasets and analytical routines, and build dashboards, reports, and visualizations that communicate testing results and areas of risk.
Support automation of manual testing and monitoring processes and explore Python, AI, machine learning, and emerging technologies for audit and compliance analytics.
Partner with Data Engineering, IT, GRC, and other technical teams to understand data sources, system functionality, and data limitations.
Document data sources, business rules, analytical logic, assumptions, and validation procedures.
Work with Internal Audit, Compliance, Funding, IT, Data Engineering, GRC, and business stakeholders to translate questions into actionable analytical requirements.
Communicate analytical results and testing findings to technical and non-technical audiences, and provide analytical support for audits, reviews, compliance assessments, and management reporting.
Build cross-functional working relationships while maintaining appropriate independence and objectivity.
Escalate complex issues, significant exceptions, and data concerns to the Senior Manager, Data Analytics or an appropriate functional leader.