Growth Analytics & Operations Lead San Francisco, CA (Hybrid) or Fort Lauderdale, FL (Hybrid) | Full-time | Individual Contributor
The RoleWe're looking for a
Growth Analytics & Operations Lead to own how Haystack measures paid growth and how the growth budget gets spent well. You will work day to day with our Growth Marketing lead, who runs the campaigns, our BD lead, our data teammate, and engineering. They set direction on channels and deals. You own the attribution stack, the LTV and payback models, the incrementality tests, the budget pacing, and the dashboards the team runs on.
This is not a reporting role. You decide what we should believe about our campaigns and placements, you catch the broken number before anyone else does, and you make the call on where the next dollar goes and back it with data.
What You'll Do- Own paid growth measurement: our MMP (AppsFlyer), SKAdNetwork, deep link tracking, and how CTV placements on Roku, Fire TV, Vizio and Samsung are measured. Check the MMP against reality and fix it when it drifts.
- Design and automate reporting systems and dashboards for revenue, partnerships, and marketing campaigns across Snowflake and third-party tools (Google Ads, Meta, etc.).
- Build the LTV, CAC and payback model by platform and device, with an early indicator we can act on within days. Design and run incrementality tests (holdout, geo, pre/post) so we know what actually moved viewing and subscriptions, not what got credited.
- Build and monitor A/B tests and experimentation frameworks with Product and Data teams, applying statistical rigor to separate causation from correlation.
- Identify and communicate actionable insights that drive user growth, partner success, and marketing ROI.
- Run budget operations: pacing, forecasting, and reconciliation across Meta, Google, Apple Search Ads and the CTV platforms. Work with the Growth Marketing lead on bid and budget changes and automate the routine ones.
- Financial modeling and potential deal analysis predicting efficacy and ROI based on inputs and historical performance. Make informed recommendations and predictions on CPI and CAC for new opportunities
- Build the checks that catch a broken pipeline or a wrong CAC number before anyone asks. Tracking integrity is yours.
- Use AI as part of how you work. Current AI tools every day to write and check queries, build automations, and pull reports together. You have built things for yourself with them and you keep up with what shipped this month.
Who You Are- Bachelor's degree in a quantitative or analytical field required (e.g. Mathematics, Economics, Statistics, Engineering); advanced degree is a plus (MBA or M.S.).
- 4 to 7 years in growth or marketing analytics, marketing operations, or media buy operations, including at least 2 years inside a paid acquisition team at a consumer app, streaming, media or gaming company.
- Data native-fluent in SQL, comfortable in Snowflake (or similar), and experienced in building analytics from 01, including automated dashboards (Looker, Mode, Tableau, or equivalent).
- Marketing Attribution Minded: You have owned or run an MMP or attribution setup (AppsFlyer, Adjust, Branch or similar) and understand SKAdNetwork, lookback windows and deep linking. You have run at least one incrementality or holdout test and can explain what changed because of it.
- Experimentation-minded-you design and interpret controlled tests, know how to evaluate statistical significance, and connect results to actionable outcomes.
- Business fluent-you think in terms of unit economics, growth levers, and ROI, not just metrics.
- Have built or maintained an LTV or payback model that a team used to make spend decisions. Python or R is a plus.
- Proactive and hands-on-you put the work on the board yourself, you implement instead of only analyzing, and you raise a flag early when something is blocked.
- Bonus: connected TV advertising, mobile gaming user acquisition, or ad-supported streaming.
- Genuinely AI native. You use current AI tools daily to write and check queries and build automations, and we will want to see it live in the interview, not hear about it.
- Not a fit if: your work ends when the chart is delivered, you need clean data before you can act, or AI is a line on your resume rather than part of how you work every day.
