Remote | Revenue Operations Specialist (SaaS) — $50–$100/hour

24-Mag•New York, NY

1d•$50 - $100•Remote

About The Position

We are sharing a specialised consulting opportunity for experienced Revenue Operations professionals with strong expertise in CRM ownership, SaaS revenue systems, compliance-constrained process design, data integrity, and operational decision-making to contribute to an advanced AI training and evaluation project. Selected professionals will assess and improve CRM data models, resolve conflicting operational policies, design compliant revenue workflows, and strengthen reporting accuracy across complex SaaS environments. The work is particularly relevant to professionals with hands-on experience in regulated or multi-product businesses where operational judgement, system ownership, and clear documentation are essential. No prior experience in AI is required.

Requirements

4+ years of direct, hands-on experience in SaaS revenue operations, sales operations, customer success operations, implementation operations, or a closely related function
Practical operational experience is required; management-only or adjacent exposure is not sufficient
Proven ownership of Salesforce, HubSpot, or another comparable CRM platform, including direct configuration experience
Hands-on familiarity with at least two additional revenue-system categories such as billing, CPQ, ticketing, or project tracking
Strong experience resolving policy conflicts and explaining operational trade-offs
Background in high-complexity or compliance-sensitive environments such as fintech, healthtech, insurtech, or comparable industries is strongly valued
Strong operational judgement when rules, regulations, technical constraints, and business requirements intersect
Experience designing processes for regulated industries or multi-product SaaS environments
Strong understanding of revenue-data integrity, reporting accuracy, and operational analytics
Excellent written and verbal communication skills
Ability to document complex logic clearly for technical and non-technical stakeholders
Comfortable navigating ambiguity and making well-reasoned decisions about process and system changes
No prior experience in AI training or model evaluation is required

Responsibilities

Assess and refine CRM data models to support evolving sales, customer success, and revenue operations requirements
Configure and evaluate CRM structures with attention to scalability, usability, and reporting integrity
Identify weaknesses in data architecture, field logic, process design, and system ownership
Apply hands-on experience with platforms such as Salesforce, HubSpot, or comparable CRM systems
Ensure CRM configuration aligns with real-world operational and cross-functional needs
Identify conflicts between operational policies, system constraints, and business requirements
Determine and document practical resolutions to competing rules or priorities
Explain the reasoning, trade-offs, and implications behind operational decisions
Apply strong judgement in situations where policies or requirements are ambiguous
Distinguish between issues that require change and processes that should remain stable
Design and validate revenue workflows operating within regulatory or compliance requirements
Evaluate processes across regulated or high-complexity SaaS environments
Balance operational efficiency with compliance, reporting, and control requirements
Identify process risks where regulatory obligations intersect with commercial workflows
Recommend scalable improvements without introducing unnecessary operational complexity
Diagnose gaps, inconsistencies, and weaknesses in revenue data quality
Improve reporting accuracy across CRM and connected SaaS revenue systems
Evaluate whether operational data supports reliable analytics and decision-making
Identify underlying process or system causes of reporting discrepancies
Recommend improvements that strengthen data integrity across interconnected tools
Deliver detailed process walk-throughs based on direct system-configuration experience
Document important decision points, operating logic, and lessons learned
Contribute written and verbal insights to scenario-based operational evaluation tasks
Explain complex operational choices clearly to both technical and non-technical stakeholders
Collaborate with project participants to refine workflows, standards, and evaluation criteria