Founding Data Analyst

Overview

SyntheticFi is a YC-backed, fast-growing company serving financial advisors with a product that helps them strengthen client retention and bring in new business. The business has been expanding by more than 20% month over month for the past year, and this role sits at the center of that growth.

We are looking for a Founding Data Analyst to support the Growth and Operations teams by strengthening the data backbone of the company. This is a high-ownership role at an early stage, with broad exposure to how the business runs and scales. You will work on data cleanup, pipeline development, metric tracking, and operational improvements that directly support decision-making.

You will collaborate closely with the founders, Tony Yang and Joseph Wang, and partner across growth, revenue, and operations. Instead of being limited to one narrow area, you will help build and improve systems that touch many parts of the company.

Key Work Areas

• Improve the core data stack used by Growth, Revenue, and Operations, including reporting, CRM/HubSpot, and analytics systems that support daily decisions.
• Work with the founders on operational analysis, including defining and monitoring SLAs for onboarding, support, and billing in a rapidly scaling environment.
• Help automate workflows with cross-functional teams, reduce manual effort, strengthen data quality, and make billing, revenue operations, onboarding, and customer support processes more scalable.

What Success Looks Like

• Source-of-truth datasets are documented, validated, monitored, and dependable enough for teams to use confidently.
• Company-wide metrics are clearly defined, tracked consistently, and used regularly in decision-making.
• Spreadsheet-heavy reporting and other manual processes are reduced.
• Teams get faster answers to business questions across the organization.

Requirements

• A bachelor's degree or higher in a highly analytical discipline such as computer science, data science, statistics, applied mathematics, or another quantitative field with programming exposure.
• Between 1 and 3 years of professional experience in data, analytics, or systems-related roles.
• Strong SQL ability, plus hands-on experience with a data-focused programming language such as Python, R, Java, Scala, or something similar.
• Advanced Excel or Google Sheets skills and comfort working with financial data.
• Strong problem-solving instincts, excellent attention to detail, and comfort working through messy real-world operational data.
• Clear communication skills and the ability to collaborate across functions.
• Familiarity with modern analytics and data engineering tools such as dbt, Airflow, Fivetran, Snowflake, BigQuery, AWS, or Azure is a significant advantage, along with the ability to learn new tools quickly.

Preferred Background

• Exposure to ETL or ELT platforms and cloud-based data architecture.
• Experience using cloud platforms such as AWS or Azure.
• Strong debugging, triage, and troubleshooting skills in complex environments.
• Experience with automation tools like Zapier or Retool, and CRMs such as HubSpot.
• Background in fintech, startups, or other high-growth settings.

Compensation and Benefits

• Base pay is $80,000 to $110,000.
• Annual bonus opportunity of up to 10% of base salary.
• Equity grant of 0.025% to 0.10% stock options, with long-term upside as the company grows.

Location and Eligibility

This is a full-time role based in San Francisco, California, with a hybrid working setup.

Candidates must be physically located in the United States. Visa sponsorship may be considered for exceptional candidates who are already based in the U.S. Preference is given to applicants in the San Francisco Bay Area.

Application Note

Because of the number of applications received, the team may not be able to reply to everyone individually. If you do not hear back within two weeks of applying, you should assume the company is not moving forward with your application at this time. The team appreciates your interest and welcomes future applications for roles that better match your background.