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Lead Data Analyst

AI Summary
Liftoff is seeking a senior individual-contributor analyst to solve ambiguous supply-side business and technical problems in a mobile AdTech platform. The role requires advanced SQL on billion-row datasets, statistical experimentation expertise, and the ability to create automated reporting and dashboards in Looker or Tableau. The analyst will translate topics such as ML changes, SDK upgrades, and auction mechanics into commercial and financial impact. They will lead cross-functional initiatives, influence senior decisions, and mentor other analysts in analytical rigor and communication.
Remote from
USA
Salary
USD 142k–195k / yr
Employment
Full Time
Experience
Director
Published
Apply before
9 Dec 2026
Listing views
43
Application actions
2
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Opportunity details

About this role.

Liftoff is a leading AI-powered performance marketing platform for the mobile app economy. Our end-to-end technology stack helps app marketers acquire and retain high-value users, while enabling publishers to maximize revenue across programmatic and direct demand.

Liftoff’s solutions, including Accelerate, Direct, Monetize, Intelligence, and Vungle Exchange, support over 6,600 mobile businesses across 74 countries in sectors such as gaming, social, finance, ecommerce, and entertainment. Founded in 2012 and headquartered in Redwood City, CA, Liftoff has a diverse, global presence.

About this role:

As a Lead Data Analyst, you will report directly to the VP of Analytics & Operations Supply and act as the team’s senior individual contributor on the hardest and most ambiguous analytical problems across Liftoff’s supply side. You will act as a technical and strategic thought leader, defining best practices for analytics, and mentoring analysts on technical rigor, problem-solving, and strategic insight development. This role demands technical depth, strong business acumen, and leadership skills to drive impact across multiple teams.

Responsibilities:

  • Drive analysis and insight generation on highly complex, ambiguous business and technical questions; influence roadmap and operational decisions at a senior level.
  • Write and optimize complex SQL queries for large-scale datasets (billions of rows), developing reproducible analytics workflows.
  • Conduct root-cause analysis and triage technical issues at the intersection of product performance and business KPIs.
  • Build and automate dashboards, ad-hoc analysis tools, and internal reporting pipelines using SQL, Looker, and/or Tableau.
  • Translate highly technical concepts (e.g., ML model changes, SDK upgrades, auction mechanics) into business impact analysis for Commercial teams and leadership.
  • Lead transformational projects end-to-end, from ideation and scoping through technical execution and operational rollout.
  • Mentor other analysts on technical best practices, business context, and effective communication.
  • Partner cross-functionally with Engineering, Product, Data Science, and Finance teams to drive initiatives forward.

Requirements:

  • B.A./B.S. degree in Analytics, Computer Science, Engineering, Mathematics, Statistics, Economics, or a related field.
  • 8+ years of experience in data analytics, consulting, or business analytics roles, preferably in high-tech or AdTech.
  • Expertise writing complex, performance-optimized SQL on massive datasets; experience with cloud data warehouses (BigQuery, Snowflake, Redshift, Trino).
  • Solid grounding in statistical inference, A/B test design, and causal reasoning; comfortable with confidence intervals, statistical power, and the failure modes of noisy experiments.
  • Proficiency with Looker, Tableau, or similar BI tools.
  • Demonstrated ability to break down ambiguous business problems into structured analyses leading to actionable recommendations.
  • Can connect a technical finding to revenue, margin, and partner impact without being told how.
  • Strong written and verbal skills; able to tailor technical concepts for a range of audiences from engineering to C-level leadership. Consulting-style structured presentation skills: you can build a narrative, defend a recommendation, and handle pushback in the room.
  • Ability to mentor others, lead cross-functional projects, and drive organizational change through data insights.

Location:

This role is eligible for full-time remote work in one of our entities: CA, CO, ID, IL, FL, GA, MA, MI, MN, MO, NJ, NV, NY, OR, PA, TX, UT, and WA.

We are a remote-first company with US hubs in Redwood City, Los Angeles, and New York City.

Travel Expectations:

We offer several opportunities for in-person team gatherings, including but not limited to project meetings, regional meetups, and company-wide events. We expect our employees to attend these gatherings at least once per quarter. These gatherings provide essential opportunities for collaboration, communication, and team building.

Compensation:

Liftoff offers all employees a full compensation package that includes equity and health/vision/dental benefits associated with your country of residence. Base compensation will vary based on the candidate’s location and experience.

The following are our base salary ranges for multiple levels:

  • SF Bay Area, Los Angeles/Orange County, NYC, Seattle: $165,000 – $195,000
  • Olympia, Austin, San Diego, Santa Barbara, Boston: $152,000 – $179,000
  • All other cities and towns in our approved states: $142,000 – $167,000

Liftoff offers a fast-paced, collaborative, and innovative work environment where employees are empowered to grow and make an impact. We’re shaping the future of the mobile app ecosystem—join us and help accelerate what’s next.

Liftoff’s compensation strategy includes competitive salaries, equity, and benefits designed to support employee well-being and performance. We benchmark compensation based on role, level, and location to ensure fairness and market alignment. Benefits may include medical coverage, wellness stipends, and additional perks based on your country of residence.

Liftoff is an equal opportunity employer. We are committed to creating an inclusive environment for all employees and applicants regardless of race, ethnicity, national origin, age, marital status, disability, sexual orientation, gender identity, religion, veteran status, or any other characteristic protected by applicable law.

Agency and Third Party Recruiter Notice:

Liftoff does not accept unsolicited resumes from individual recruiters or third-party recruiting agencies in response to job postings. No fee will be paid to third parties who submit unsolicited candidates directly to our hiring managers or Recruiting Team. All candidates must be submitted via our Applicant Tracking System by approved Liftoff vendors who have been expressly requested to make a submission by our Recruiting Team for a specific job opening. No placement fees will be paid to any firm unless such a request has been made by the Liftoff Recruiting Team and such a candidate was submitted to the Liftoff Recruiting Team via our Applicant Tracking System.

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This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

5/5
EasyHard

Pace & Pressure

5/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

5/5
IndependentCollaborative
AI insightThis is a lead-level role requiring 8+ years of experience, expert SQL at large scale, sound causal and experimental reasoning, and ownership of highly ambiguous strategic questions. Success depends equally on technical depth, commercial judgment, executive influence, and mentoring capability.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job median (per year)Market rate
$168,500
US market range (per year)$145k–$205k
AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. The employer discloses location-based base salary ranges of $142,000–$195,000 USD. The posting does not explicitly state a cadence, so the yearly period is inferred from the senior full-time US role and the stated base-pay amounts. The combined midpoint is $168,500 annually; a reasonable estimated US market range for a lead data analyst in AdTech is $145,000–$205,000 annually, excluding equity and benefits.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you investigate a sudden decline in supply-side revenue while separating auction, product, and partner causes?

I would first validate the metric definition and data freshness, then decompose revenue into volume, fill rate, bid density, win rate, eCPM, and partner mix. I would segment the change by geography, app, inventory format, SDK version, exchange path, and time, identify the earliest meaningful break, and compare it with releases or partner changes. I would quantify the contribution of each driver and present prioritized hypotheses with validation steps and expected business impact.

Describe how you would evaluate the causal impact of an SDK upgrade on publisher monetization.

I would prefer a randomized rollout with pre-defined primary metrics such as revenue per mille, fill rate, latency, and retention-adjusted revenue. I would perform power calculations, check treatment balance and instrumentation quality, and analyze confidence intervals rather than relying only on point estimates. If randomization were not possible, I would use a quasi-experimental design such as difference-in-differences with carefully selected controls and explicitly communicate remaining assumptions.

What practices do you use to keep complex SQL analyses reproducible and performant on billion-row datasets?

I use modular, version-controlled SQL with clear metric definitions, documented grain, data-quality checks, and reusable intermediate models. For performance, I reduce scanned data through partition filters and selective columns, avoid unnecessary joins and repeated calculations, inspect query plans, and materialize durable intermediate tables when appropriate. I also validate outputs against control totals before sharing conclusions.

How would you explain an ML model change that improves a technical ranking metric but reduces a commercial KPI?

I would frame the result around the business objective rather than the model metric alone. I would quantify the relationship between the ranking change and downstream effects such as auction participation, win rate, eCPM, revenue, and partner distribution, then identify affected segments. I would recommend whether to adjust the model objective, introduce constraints, run a targeted experiment, or accept the trade-off based on its measured commercial value.

How do you mentor analysts while maintaining high standards for analytical rigor?

I establish shared expectations for problem framing, metric definitions, statistical validity, code review, and executive-ready narratives. I use reviews as coaching sessions: I ask analysts to articulate assumptions, alternatives, and the decision their analysis supports, then provide specific feedback and reusable examples. Over time, I delegate increasingly ambiguous work while remaining available for strategic guidance and quality assurance.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
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