Confidential
Website:
confidential.careers
Job details:
Job Title: Product Business Analyst - Regulatory Analytics (Independent Contractor, Remote)
Company: US-based SaaS company
Location: Remote (Must work US hours: 9am - 5pm Eastern Time)
Compensation: $2,000 - 2,500 per month USD
Overview
We are engaging an independent contractor to provide specialized analytical and regulatory expertise to support automated compliance reporting across global pay transparency and workforce reporting requirements.
This engagement focuses on translating country-specific regulatory guidance into clearly defined, testable analytical logic and data transformations. The contractor will deliver documented business logic, Python-based data transformation scripts, validation outputs, and supporting documentation that can be implemented within a compliance analytics platform.
Deliverables
Regulatory Interpretation and Logic Definition
- Analyze country-specific regulatory guidance, such as pay gap reporting requirements.
- Translate regulatory requirements into clearly documented, testable business logic.
- Define quantitative metrics and calculation rules required for compliance.
- Maintain structured mappings between regulatory requirements, analytical logic, and technical outputs.
Data Transformation and Analytics
- Develop Python scripts to transform standardized HRIS and payroll datasets into regulator-ready analytical outputs.
- Design logic for data normalization, aggregation, and metric calculation across large datasets.
- Deliver scripts that are production-ready, documented, and reproducible.
Documentation
- Provide auditable documentation covering:
- Regulatory interpretations
- Business logic definitions
- Data transformation steps
- Assumptions and edge-case handling
- Ensure documentation is sufficient for engineering implementation, validation, and future maintenance.
Testing and Validation
- Execute validation testing to confirm analytical outputs meet regulatory requirements.
- Produce data-quality and error reports identifying invalid or non-conforming inputs.
- Stress test scripts using large or imperfect datasets to ensure stability and performance.
Collaboration and Knowledge Transfer
- Collaborate with engineering, regulatory, and QA stakeholders for clarification and implementation alignment.
- Provide analytical clarification and technical explanations to client-facing teams when needed.
- Participate in limited customer-facing discussions for technical clarification of analytical outputs, as requested.
- Support structured feedback sessions to inform improvements to logic and validation rules.
Required Expertise
- Strong Python skills for data transformation and analytical workflows.
- Demonstrated experience working with HRIS and payroll data structures.
- Proven ability to translate complex regulatory or policy requirements into executable analytical logic.
- Experience validating analytics for compliance or regulatory use cases.
- High attention to accuracy, traceability, and documentation quality.
- Ability to explain analytical and regulatory concepts clearly to non-technical stakeholders.
- Comfortable collaborating with distributed, cross-functional teams.
Preferred Experience
- Pay transparency, pay equity, workforce reporting, or employment compliance analytics.
- Large-scale data processing and performance optimization.
- Regulated environments requiring auditable and defensible outputs.
- Exposure to analytics or compliance-focused SaaS platforms.
Engagement Expectations
- Work is deliverables-based and milestone-driven.
- Contractor determines methods and execution approach.
- No exclusivity requirement.
- No benefits, employment rights, or guaranteed ongoing work.
- Contractor is responsible for applicable taxes and statutory obligations in their jurisdiction.
- Secure handling of sensitive data is required, including use of approved systems and adherence to confidentiality and data protection requirements.
What Successful Delivery Looks Like
- Regulatory requirements are converted into clear, well-documented analytical logic.
- Scripts produce accurate, regulator-ready outputs across jurisdictions.
- Deliverables handle large and imperfect datasets without failure.
- Documentation enables efficient implementation and validation by engineering teams.
- Regulatory changes can be incorporated with minimal rework.
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