Mobile User Acquisition Manager (Product)

About us:

We are a Ukrainian product IT company launching dozens of mobile apps across various niches every month. Currently, we are rapidly expanding our portfolio and looking for a skilled User Acquisition Manager.

We are building our UA department from the ground up, so we’re searching for someone ready to take full ownership of the entire cycle: from creative ideation to deep ROAS analysis.

Responsibilities:

• Launching campaigns for new products. We release new apps regularly. Within 1–2 weeks of launch, you’ll dive into the product, build audience hypotheses, run initial campaigns, and define the strategy. No hand-holding or "top-down" commands required.
• Managing media buying from zero to profitable scale. Meta, Google Ads, Unity Ads, and ASA form an ecosystem. You understand how channels influence each other and don't compare Meta’s CPI to Google’s directly.
• Analyzing cohorts. If D7 retention drops, you dive into the MMP and slice data by sources, placements, creatives, and geos until you find the root cause. Unexplained anomalies should bother you.
• Collaborating with Creative Managers as an analyst. You provide data-driven insights: which angle worked, which segment isn't converting, and what hypothesis to test next. Creativity here is driven by numbers.
• Working with the Product Team on the entire funnel. If the traffic is high-quality but onboarding is broken, you bring the data to the Product Manager. The "my job ends at the install" mindset doesn't work here.
• Early problem detection. If you spot an anomaly on a Saturday night, you investigate. You don't just report a problem; you bring an analysis and potential solutions.

Requirements:

• 2+ years in Mobile UA. Proven track record with specific products, budgets, and results. You can articulate what you launched, how you scaled it, what broke, and how you fixed it.
• Deep understanding of attribution and its flaws. You know why SKAN differs from reality (postback delay, crowd anonymity, null postbacks). You can explain the difference between last-click, probabilistic, and view-through, and where each model falls short.
• Hands-on MMP experience. Direct experience with AppsFlyer or Adjust: cohort reports, data slicing, and reconciling data with ad dashboards—without needing an analyst's help.
• Proficiency in unit economics. You understand that Blended CAC and Paid CAC are different metrics and know when to apply each. You know D7 ROAS doesn't equal cohort payback, and LTV is a model with specific assumptions you can identify.
• Structured hypothesis formulation. Instead of "let's try a new creative," you say: "CTR is fine, but Install CR is dropping on iOS—let's split by ad sets with fixed placement and compare." You think in variables.
• AI for creatives. You generate and iterate on draft visuals yourself. When a task goes to a designer, the brief includes a reference, a hypothesis, and success criteria.

You're a match if:

• You open the MMP as soon as you see a data discrepancy, not when asked.
• You can explain SKAN vs. MMP discrepancies off the top of your head because you've dealt with them before.
• When asked "why did ROAS drop?", you show data (audience, placement, creative fatigue, seasonality) rather than blaming "the algorithm."
• You have stories like: "This source has 40% worse D30 retention—kill it," and you can demonstrate the path to that decision.
• You never scale a campaign until you understand what happens after the install.

This role is NOT for you if:

• You create "catchy" creatives based on intuition rather than data-backed success.
• You believe attribution is the sole responsibility of an analyst or an MMP vendor.
• You’ve only worked with one or two channels and aren't confident in mastering new ones quickly.
• You’re satisfied with a ROAS that "looks okay" without explaining why.