Data Analyst Job at Two Dots, San Francisco, CA

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  • Two Dots
  • San Francisco, CA

Job Description

Join Two Dots to build a stronger financial system:

Every time someone applies for a mortgage, car loan, or apartment lease, they submit financial documents that humans use to build a financial profile about them. The quality of these financial profiles is a key input that regulates the body temperature of the economy.

Two Dots is building a better system to build these financial profiles more consistently and fairly with conversational interfaces that interact with consumers and automate much of the back and forth document collection process in loan and lease origination. We're building a better system to evaluate consumers consistently and fairly. We prevent fraud that humans can't see, help applicants navigate documenting complex financial situations, and surface value in atypical applications that would otherwise be discarded.

Role Overview

Two Dots is looking for a Data Analyst to transform data into actionable insights that drive product decisions and business growth. As a YC-backed, Series A company scaling rapidly, you'll work directly with product, engineering, and business teams to uncover patterns in our underwriting data, measure product performance, and identify opportunities to improve our platform.

You'll be the go-to person for understanding how our AI-powered underwriting system performs in the real world—translating complex data into clear visualizations and recommendations that shape our product roadmap.

What You'll Do

  • Write SQL queries to extract, transform, and analyze data from our Postgres and BigQuery databases

  • Build dashboards and visualizations that make complex underwriting metrics accessible to product and business stakeholders

  • Generate product insights by analyzing user behavior, conversion funnels, and underwriting performance

  • Partner with product and engineering to define and track key metrics, run A/B tests, and measure feature impact

  • Identify trends and anomalies in application data that inform risk models and product improvements

  • Create reports that communicate findings clearly to both technical and non-technical audiences

  • Support business development with data-driven presentations and ROI analyses for enterprise clients

What We're Looking For

  • Strong SQL skills – you're comfortable writing complex queries with joins, aggregations, and window functions

  • Data visualization experience – proficiency with tools like Tableau, Looker, Metabase, or similar platforms

  • Analytical mindset – you ask good questions, spot patterns, and translate data into actionable recommendations

  • Communication skills – you can explain technical findings to non-technical stakeholders

  • Attention to detail – accuracy matters when analyzing financial and risk data

  • Bonus: Experience with Python or R for statistical analysis

  • Bonus: Familiarity with fintech, lending, or real estate data

  • Bonus: Understanding of A/B testing and experimental design

Our Stack

  • Databases: Postgres, BigQuery, Redis

  • Scripting: Python, Node.js

  • Cloud: GCP

What You Get in Return

  • An opportunity to revolutionize the real estate leasing industry and own analyses that directly shape product decisions

  • Direct access to leadership and the ability to influence company strategy with your insights

  • An environment with a work culture based on trust, ownership, flexibility, and a growth mindset

  • A competitive salary, comprehensive equity package, and substantial benefits

Closing

Two Dots is an equal opportunity employer. We aim to build a workforce of individuals from different backgrounds, with different abilities, identities, and mindsets. Even if you do not meet all of the qualifications listed above, we encourage you to apply!

Compensation is variable and is subject to a candidate's personal qualifications. For this role, we offer the following base salary range (in addition to equity and full benefits): $100k - $175k per year.

Job Tags

Full time,

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