Revenue Analytics & Sales Process Analyst

The Revenue Analytics & Sales Process Analyst will build the company's revenue operating foundation by connecting sales activity, business processes, CRM data, and performance analytics.

The person in this seat will design the reporting environment, stand up and own the CRM, automate the manual steps in the lead-to-client lifecycle using AI connectors, skills, agents, and workflows, and support inbound and outbound pipeline activity directly to support compliance supervision across different functions.

This is a build role. Success depends less on operating an existing system than on constructing one from fragmented inputs and then documenting it well enough that the company can rely on it.

Primary Responsibilities

Revenue Analytics and Reporting 

• Build the company's reporting structure from the ground up, integrating CRM, accounting, and operational data sources to replace fragmented manual reporting.
• Analyze pipeline, sales activity, conversion, and revenue performance across all business lines implementing heightened compliance supervision and procedures according to regulations and internal policies.
• Define and monitor revenue and operational KPIs, including conversion rates by stage and source, sales cycle length, activity-to-outcome ratios, and revenue per client.
• Design and maintain executive dashboards and a standing weekly and monthly reporting cadence for leadership.
• Translate performance into drivers, risks, and recommended actions rather than reporting figures alone.
• Produce client- and segment-level forecasts using historical activity, seasonality, and behavioral patterns to support revenue planning. Separate it by business lines, activities, and department
• Analyze client, product, and territory performance to surface declining relationships, portfolio gaps, dormant accounts, and growth opportunities.
• Identify pipeline bottlenecks, missed follow-ups, and stalled opportunities, and quantify what they cost.

CRM Implementation and Data Management 

• Own the CRM as the system of record for leads, opportunities, clients, and revenue.
• Configure and maintain pipeline stages, deal properties, lifecycle stages, custom fields, and required-field logic so that reporting is possible in the first place.
• Migrate and reconcile data from existing spreadsheets, email, and legacy systems into the CRM, resolving duplication and gaps in the process.
• Design and enforce data standards: deduplication, naming conventions, ownership assignment, source attribution, and required data at each stage transition.
• Manage the client list — segmentation, tiering, relationship mapping, and identification of cross-sell and re-engagement candidates across the company's affiliated business lines.
• Build reporting objects and revenue tracking inside the CRM so leadership can self-serve routine questions.
• Train users on the CRM process and hold the team to the data-entry standards the reporting depends on.
• Implement systems for client documentation, privacy recordkeeping, updates info, and disclosures and communication review and archive.

AI, Automation, and Workflow Design 

• Design and implement automated processes using AI connectors, skills, agents, and workflows to remove manual work from the revenue cycle.
• Build and maintain connectors between the CRM and adjacent systems — email, calendar, document storage, e-signature, marketing, and accounting — so data flows without re-keying creating a traceable log of information flows and reports, while maintaining total privacy and security in connection and data.
• Develop reusable AI skills for recurring tasks: lead research and enrichment, meeting note capture and summarization, follow-up drafting, data hygiene checks, list segmentation, and report narrative generation.
• Deploy agents for multi-step processes that would otherwise consume analyst time, with defined inputs, outputs, and stopping conditions.
• Embed AI into CRM workflows — record enrichment, activity summarization, next-best-action prompts, and flagging of at-risk or dormant opportunities.
• Define human review checkpoints. Any AI output that reaches a client, or that feeds a decision with financial or regulatory consequence, passes through a person before it goes out. Follow or create company details procedures and workflows for each process and solutions available to increase efficiency and reduce mistakes in human processes.
• Document every automation: what it does, what it touches, what triggers it, who owns it, and how it fails.
• Evaluate AI output quality on an ongoing basis and retire or rebuild processes that drift.
• Assess new tools and capabilities against actual process needs, and recommend adoption or rejection with reasoning.

Sales Pipeline Support 

• Support inbound and outbound pipeline activity, including lead segmentation, qualification, follow-up coordination, and funnel performance tracking to grow our firm headcount in revenue sales force in different business lines, not for B2C clients.
• Route and prioritize inbound leads against defined qualification criteria.
• Build and maintain outbound target lists and sequences, coordinating with Business Development on messaging and cadence defined as potential producers for the new business lines of the Firm.
• Track follow-up commitments so that no qualified opportunity goes dark for lack of a next step.
• Prepare pre-meeting research and account briefs for Business Development.
• Support development of Spanish-speaking and Latin American client segments through market research, account analysis, and opportunity assessment.
• Maintain the handoff process between compliant marketing resources, sales, and client onboarding so context travels with the record.

Process and Documentation

• Map current-state processes across the lead-to-client lifecycle and identify gaps, redundancies, and manual steps worth eliminating.
• Build a structured operating system for follow-up, decisions, dependencies, ownership, and next actions, reducing information loss across email, messaging, and spreadsheets.
• Write and maintain process documentation and standard operating procedures for the revenue functions this role touches to assist supervisory principals in reviews or updates to reporting or changes in current existing or new documentation.
• Establish a change process for CRM configuration and automation so modifications are tested and recorded rather than made live and forgotten.
• Maintain a prioritized backlog of process improvements, ranked by time recovered or revenue affected.
• Search for integration proprietary safe solutions between CRM and other approved software tools in the business

Compliance and Recordkeeping

The company operates in a regulated environment, and this role sits close to client-facing communications and records. The person in this seat is expected to:

• Understand that business-related electronic communications are subject to retention requirements, and design automations so they capture rather than bypass the record.
• Route any AI-generated or AI-assisted client communication, marketing content, or social media material through the firm's designated principal for review before use. This is not a judgment call the analyst makes independently.
• Handle client personal and financial data in accordance with the firm's privacy and information security policies, with particular care in what data is exposed to third-party AI tools.
• Escalate promptly when an automation, data flow, or vendor relationship raises a question about recordkeeping, supervision, or client privacy.

No prior securities industry experience is required. Willingness to learn the constraints and work within them is.

Qualifications

Required

• Bachelor's degree in computer information systems, computer science, business analytics, or a related field.
• Two or more years of experience in revenue operations, commercial or sales analytics, or business intelligence, including responsibility for building reporting rather than only consuming it.
• Demonstrated experience constructing a reporting environment from fragmented sources — integrating ERP, database, and spreadsheet data into a consolidated analytics layer.
• Strong SQL and data modeling capability, with hands-on experience in a modern BI platform (Power BI, including DAX and Power Query, or equivalent) and advanced Excel.
• Experience designing commercial tracking and follow-up workflows for customer activity, open actions, dependencies, and next steps — including in environments without a formal CRM in place.
• Applied experience with AI tools in a working context, including prompt design, workflow construction, AI-assisted development, and realistic assessment of where AI output can and cannot be trusted.
• Forecasting experience at customer or product level using historical demand, seasonality, and behavioral data.
• Cross-functional working experience with sales, marketing, operations, and IT to define KPIs, resolve data quality issues, and standardize reporting logic.
• Spanish and English professional proficiency.
• Ability to work independently and set priorities in an environment without established process.

Preferred

• Formal training or postgraduate coursework in artificial intelligence or machine learning.
• HubSpot experience, or demonstrated capacity to learn and administer a CRM platform quickly. Direct HubSpot administration experience is not required; the ability to configure, own, and document a CRM is.
• Experience building internal tools or applications (JavaScript, React, or similar), including defining requirements, testing, and roadmap.
• Documentation and knowledge-management platform experience (Notion or equivalent).
• Familiarity with Latin American, Caribbean, or Spanish markets and client relationships.
• Experience in financial services, wealth management, real estate, or another regulated or relationship-driven sales environment.
• Experience standing up a revenue function or CRM from a greenfield state.

First-Year Outcomes

Success in the first twelve months looks like:

• A CRM standing up in the first quarter, populated, deduplicated, and configured so that pipeline and revenue reporting requires no manual reconciliation.
• A consolidated reporting layer replacing manual spreadsheet reporting, with a standing executive cadence delivered on schedule without being chased.
• A documented map of the lead-to-client lifecycle, with the highest-friction manual steps automated.
• A working library of AI skills, connectors, and workflows in production, documented well enough that someone else could operate them.
• Measurable improvement in follow-up discipline and a reduction in stalled or dormant opportunities.
• Revenue opportunities in the existing client base identified from data rather than recollection, and handed to Business Development as qualified next steps.