Sr. Data Analyst

Pilot.com•San Francisco, CA

1d•$126,000 - $170,000•Hybrid

About The Position

Pilot is hiring a Senior Data Analyst to own our marketing analytics and uplevel our data-driven decision-making as we embark on the fastest-growing and quickest-evolving time in our company’s history. Pilot has spent years providing reliable back office services to over 3,000 businesses so they can focus on running their business. This year we announced our AI accounting platform, Meridian, and it has quickly become an industry leader because it was built with the nearly a decade of experience Pilot has building a platform for accountants and providing high quality accounting services. While this new product is exciting, it comes with a plethora of new complexity as we strive to grow our current back office services while also rapidly growing our AI platform clientele. Marketing is the biggest single driver of our revenue and is our largest spend line. With Meridian, our marketing motion is rapidly changing: more events, more brand investment, and more channels. With this, attribution, tracking, and reporting get harder and harder but more and more important. We need someone experienced and knowledgeable in the domain to lead our analytics to where it needs to go. As a Senior Data Analyst, you will work closely with the marketing team and company leadership to own marketing analytics across attribution, channel economics, experimentation, and incrementality. You will identify which channel dollars are paying off and how we should reallocate our budget to maximize revenue efficiency. Most importantly, you will own closing the gap between us being data-informed and having a data-driven marketing engine. This is a strong fit for someone who strives to turn data and analytics into actionable insights and tangible impact, and who works with high-level leaders not just as a consumer of their data asks, but as a partner in finding the right data solutions. Pilot’s data stack is Snowflake, dbt, and Looker, with Marketo, Marketo Measure, and Salesforce on the marketing side. We are active users of Claude Code to make our processes more efficient and our output more prolific.

Requirements

5+ years in analytics, including owning a business domain and the stakeholder relationships in it
Deep marketing analytics experience: channel performance across paid and organic, the funnel from lead through closed-won, and the unit economics on top of it
Has built or replaced an attribution model, and can explain where it breaks down
Experience designing and reading out incrementality tests, whether geo, holdout, or comparable, including the statistical work in Python or R
Designs the comparisons and controls a finding needs, and states plainly what the data does and does not support
Strong SQL, and builds reporting in Looker or a comparable BI tool that non-analysts use on their own. Comfortable building and extending models in dbt, or able to pick it up quickly
Works directly with executives, including reframing a request that will not answer the underlying question

Nice To Haves

Media mix modeling or other top-down measurement experience
Marketo and Marketo Measure, or comparable marketing automation and attribution tools
Salesforce, including campaign influence reporting
Ad platform APIs, PartnerStack, GA, or other spend and engagement sources
Brand or offline measurement experience
ABM account funnel work
Production dbt experience
B2B SaaS with both sales-led and self-serve motions
Fintech, accounting software, or professional services background

Responsibilities

Own attribution: make campaign-level multi-touch attribution usable and move marketers off Salesforce campaign influence reporting
Own channel efficiency at the top of the funnel: cost per lead, per SQL, and per pipeline dollar by channel and campaign group, and recommendations on where to allocate the next dollar
Design, run, and report on incrementality tests, including holdout and geo tests
Measure brand and event channels: podcast and conference sponsorships, advertorial, webinars, and brand spend. Group channels where a channel-by-channel read is not possible, and use observed lift where a controlled test is not available
Own marketing unit economics: LTV, CAC, and CAC payback by segment, cost to serve, and the ideal customer profile for our direct business
Build GTM analytics for our new product line as deal volume arrives: lead scoring, closed-lost analysis, and engagement depth
Support lifecycle and nurture marketing: measurement for a team that does not source its own leads, and driver analysis on re-engagement
Define the marketing data model: the sources, metrics, and models the work depends on. Build them in dbt where you can, and partner with our analytics engineer on ingestion and the heavier platform work
Build reporting that marketers can run on their own for campaign and channel performance
Partner with marketing leadership in their planning and budget cycles, and take on work outside marketing when the business needs it