Sr. Data Analyst

Pilot.com•San Francisco, CA

16h•Hybrid

About The Position

Pilot is hiring a Senior Data Analyst to own our marketing analytics and enhance data-driven decision-making during a period of rapid growth. Pilot, known for its back-office services to over 3,000 businesses, has launched an AI accounting platform, Meridian, which has become an industry leader. This expansion brings complexity as the company grows both its back-office services and its AI platform clientele. Marketing is a primary driver of revenue and the largest spend category. With Meridian, marketing strategies are evolving with increased events, brand investment, and channel diversification, making attribution, tracking, and reporting more critical. The company seeks an experienced individual to lead analytics efforts, partnering with the marketing team and leadership to manage attribution, channel economics, experimentation, and incrementality. The goal is to identify effective channel investments, optimize budget allocation for revenue efficiency, and transition from being data-informed to having a data-driven marketing engine. This role is ideal for someone who can translate data into actionable insights and tangible impact, collaborating with senior leaders as a partner in finding data solutions. Pilot's data stack includes Snowflake, dbt, and Looker, with Marketo, Marketo Measure, and Salesforce for marketing. Claude Code is used for process efficiency. The role is hybrid, requiring 3 days per week in the San Francisco office (Mondays, Tuesdays, and Thursdays).

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