Data Operations Analyst

Position Overview 

SyntheticFi is growing at an extraordinary 20%+ MoM over the past year, powered by a product that our target customers - financial advisors (RIAs) - already view as a true differentiator for their practice, helping them retain AUM and win new clients. 

With a proven product and strong inbound demand, we’re now at an inflection point. As we scale, maintaining clean, reliable data and scalable systems across the business is critical to sustaining that growth.

We are hiring a Data Operations Analyst to join our Operations team. This role sits between SyntheticFi’s operations and go-to-market teams, owning the systems and data infrastructure that power SyntheticFi’s operations and go-to-market execution. 

You’ll work directly with our cofounders, Tony Yang and Joseph Wang, to ensure our internal tools, data flows, and reporting systems are accurate, efficient, and scalable.

As a Data Operations Analyst, you will:

• Build and own core internal systems on GTM and Operations, including HubSpot / CRM, performance reporting, and various other analytics needs;
• Monitor and optimize operations processes; create and track SLAs across operations (onboarding, support, etc.)
• Design workflows to improve efficiency and reduce manual work; this includes billing and accounts receivable workflows, financial operations processes, etc. 

What Success Looks Like:

• Clean, reliable data across all core systems; teams trust dashboards and reporting to make decisions
• Operational processes, especially financial operations, are efficient, consistent, and scalable

Required Qualifications

• Bachelor’s degree in an analytical field
• 1–3 years of experience in operations, data, analytics, or systems roles
• Strong Excel / Google Sheets skills and comfort working with financial data
• Familiarity with data tools (SQL, Python, etc.)
• Exceptional attention to detail and accuracy
• Strong problem-solving ability and willingness to dig into messy data
• Ability to manage multiple workflows and prioritize effectively
• Strong communication skills and ability to work cross-functionally

Preferred Qualifications 

• Experience in fintech, startups, or high-growth environments
• Familiarity with automation tools (Zapier, Retool, etc.)
• Experience working with CRMs (HubSpot preferred) or similar systems

Compensation 

We care about talent, and we show it. SyntheticFi offers a top-tier compensation and benefits package with meaningful options upside. 

• Base Salary: $70,000 - $80,000
• Bonus: up to 10% of base salary. 
• Stock option compensation: 0.025%-0.10%.

About SyntheticFi 

SyntheticFi was founded by Tony and Joseph after recognizing a critical gap in the market: affordable borrowing options for advisors and their clients. Drawing on deep expertise in both finance and technology, we built the first viable securities-backed line of credit product powered by box spreads, an institutional borrowing strategy now made accessible at scale. Since launch, SyntheticFi has grown at an extraordinary pace, sustaining 20%+ MoM growth, and is the category-defining leader in wealthtech.

SyntheticFi is a YC company with a recent round from partner RIAs and wealth-tech VCs (Ritholtz, Social Leverage, NextGenVP / Brown Advisory). 

Application Process

To apply, please email hiring+dataops AT syntheticfi.com, with:

• Your resume,
• Your LinkedIn profile / personal website,
• A brief example of a system, dashboard, or process you’ve built or improved

Subject line: Application - Data Operations Analyst - [Your Name]

If you were referred by a mutual contact, please include that in your email. 

Note: Applications without the requested materials will not be considered. 

Location and Work Authorization

SyntheticFi is a U.S.-based team, and we are currently prioritizing candidates who are physically located in the United States.

SyntheticFi is open to sponsoring visas for exceptional candidates who are currently based in the United States.

SyntheticFi has a preference for candidates in the following metro areas:

• San Francisco Bay Area
• Orlando, FL
• Greater Los Angeles
• Madison, WI
• Dallas, TX
• Bangor, ME