Data Analyst

Zero Homes

• $120K — $150K *
Business Services
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 3-6 years in data analytics or analytics engineering, preferably in a high-growth company.
  • Proficient in SQL with strong data modeling skills.
  • Experience with Python or R for analysis and familiarity with version control.
  • Understanding of business processes such as funnels, operations, and customer experience.
  • Excellent communication skills for presenting findings and making complex analyses accessible.
  • Intellectual honesty in reporting data insights, regardless of preconceived narratives.
  • Familiarity with AI tools to enhance data query processes.

Responsibilities

  • Build and maintain core datasets across multiple platforms including HubSpot and PostHog.
  • Own end-to-end data quality, ensuring measurability from day one and preemptively fixing issues.
  • Document metrics and processes for standardized data understanding.
  • Conduct meaningful analyses on funnel conversions, cycle times, and capacity utilization.
  • Investigate root causes of data fluctuations and effectively communicate insights.
  • Support measurement of experiments and collaborate with Growth and Sales teams.
  • Create self-serve reporting tools for recurring business questions.

Benefits

  • Equity participation in the company's growth.
  • Medical, dental, and vision insurance coverage.
  • Generous PTO policy of 4 weeks plus unlimited sick days.
  • Flexible in-office work schedule with the possibility for remote work.
  • Workstation stipend for home office setup.
Full Job Description
About the Role & Your Impact

We're looking for a Data Analyst to build the foundation the rest of the company thinks on. Reporting to the Sr. Manager of Business Operations, you'll turn the data flowing through every part of Zero (sales, marketing, fulfillment, supply chain, and finance) into trusted, queryable, reusable datasets and the analysis that runs on top of them.

Today our data lives in a lot of places: HubSpot, PostHog, our platform, spreadsheets, and program partner files. That means good questions take too long to answer and the same number sometimes comes back three different ways. Your job is to fix that at the root, then use it: model the data properly, make it accessible, and do the analysis that turns it into decisions. You'll be the person the team trusts when the number matters.

What You'll Do

Data Foundations

  • Build and own our core datasets: model data across HubSpot, PostHog, our platform, and financial and operational sources into clean, documented tables everyone can rely on.
  • Own data quality end to end: instrument new processes so they're measurable from day one, and find and fix the breaks before someone else finds them in a board deck.
  • Document metrics, definitions, sources, and methods so numbers mean the same thing to everyone and analyses are reproducible.
  • Reduce the cost of every future question by leaving the data model better than you found it.


Analysis

  • Do the analysis, not just the plumbing: funnel conversion by market and channel, install throughput and cycle times, capacity utilization, cohort behavior, and unit economics.
  • Get to root cause. When a number moves, you dig through the layers (data, process, and people) until you understand and communicate why.
  • Support experiment and program measurement, partnering with Growth and Sales on what actually moved the outcome.
  • Deliver clear, decision-ready findings with quantified impact, not just charts.


Enablement & Tooling

  • Make the business self-serve: build the reporting and tooling that answers recurring questions without a human in the loop.
  • Build durable tooling rather than one-off spreadsheets, so the work compounds instead of expiring.
  • Help teams ask better questions of the data, and be the person they trust when the number matters.
  • Leverage AI tools to compress the time between question, query, and answer.


What You Bring

  • 3-6 years in data analytics, analytics engineering, or a similarly technical analytical role, ideally at a high-growth company.
  • Strong SQL. You write it daily, you can model data (not just query it), and you know why a number is wrong before someone tells you it is.
  • Real technical range: Python or R for analysis, comfort with version control, and the ability to build something durable rather than a one-off spreadsheet.
  • Business sense beyond the numbers: you understand how funnels, field operations, and customer experience actually work, and you pick the questions worth answering.
  • Strong communication skills: you can present findings to leadership, make a complex analysis feel simple, and land a recommendation.
  • Intellectual honesty: you report what the numbers say, including when they contradict the popular narrative or your own prior analysis.
  • You've AI-enabled yourself to move fast across whatever stack you land in.


Nice to Have

  • Experience in home services, energy, construction tech, marketplaces, or businesses with physical operations.
  • Experience building a data stack from an early stage (warehouse, transformation, BI) rather than inheriting one.
  • Experience with PostHog or other product analytics tooling.
  • Experience with job costing, project-based economics, or external partner reporting.


$120,000 - $150,000 a year

Equity

🩺 Medical, Dental, and Vision

4 Weeks PTO + unlimited sick days

Primarily an in-office role, with a flexible schedule

Workstation stipend

Pay offered may vary depending on multiple individualized factors, including job-related knowledge, skills and experience. This role also includes meaningful equity compensation so successful candidates can participate in our company's accelerating growth.

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