Sr. Data Analyst

Who We Are (Mode.Inc)
Mode is a fast-growing technology company building businesses at the intersection of AI, data, mobile apps, and digital experiences. Our portfolio of mobile apps and digital products reaches 100M+ monthly active users across a global audience. We continue to accelerate growth through product innovation, strategic acquisitions, and emerging business opportunities.
Who We Are (Mode.Inc)
Mode is a fast-growing technology company building businesses at the intersection of AI, data, mobile apps, and digital experiences. Our portfolio of mobile apps and digital products reaches 100M+ monthly active users across a global audience. We continue to accelerate growth through product innovation, strategic acquisitions, and emerging business opportunities. Mode was recognized by Deloitte as the
#1 fastest-growing software company in North America
on the **** Technology Fast 500. Today, we are building our next phase of growth, including expanding Mode's AI and data business and developing direct relationships with companies that can benefit from the data and capabilities we have built.
Our Team and Culture Drive Our Success
Our team is the heart of our culture. We value innovation, collaboration, and curiosity, with a passion for getting things done. We strive to hire and cultivate the best team members and foster a culture of open communication and transparency. We are driven and hard-working but also committed to having fun along the way. We allow OKRs to guide us, assume positive intent, sometimes agree to disagree and commit, honor our commitments, seek to accomplish more with less, and encourage everyone to speak up as our team owns our company's success. You can read more about our team and how we work here.
About the Role
We're looking for a Senior Data Analyst to be the analytical partner to our User Acquisition team. You'll own the measurement of how we acquire users across our portfolio of mobile apps and web properties — from attribution and channel performance to cohort LTV and payback — and turn that into clear recommendations on where to spend the next dollar. The ideal candidate has exceptional analytical skills, strong SQL and Python skills, deep familiarity with mobile app marketing data, and can bring rigor to data quality, analysis and storytelling.
Design, build, and maintain common datasets and data pipelines that strengthen self-service analytics and enable data-driven decision making across the organization
Improve data quality, accuracy, reliability, and documentation to strengthen self-service analytics
Own UA performance measurement across paid channels (e.g., Meta, Google, TikTok, AppLovin, Unity), including CPI/CAC, ROAS, retention, and payback by channel, campaign, geo, and creative
Build and maintain predictive LTV models and cohort curves that let the UA team make bid and budget decisions on early signals
Reconcile and validate data across MMPs, ad networks, and internal event data, and investigate discrepancies in attribution, installs, and revenue
Analyze web-to-app and web funnel performance, from landing page to install to first reward or engagement, and identify where users drop off
Design and read incrementality tests, geo-holdouts, and creative or landing-page A/B tests to measure true lift beyond last-touch attribution
Monitor traffic quality and flag anomalies, including fraud, low-quality sources, and post-install behavior that doesn't match expectations
Partner with the UA team on budget allocation and channel mix scenarios, and translate findings into clear spend recommendations
Analytical excellence to dissect complex, ambiguous problems and uncover actionable insights
Solid SQL and Python programming skills, and experience working with large-scale production data
Business acumen to translate data and analysis into business impact
Exceptional written and verbal communication skills to effectively collaborate in a highly cross-functional environment
4+ years in analytics, with at least 2 years supporting user acquisition or performance marketing for mobile apps
Hands?on experience with at least one MMP (AppsFlyer, Adjust, Singular, or Branch) and an understanding of attribution windows, re?engagement, and postbacks
Experience building dashboards, LTV/payback models and cohort analyses
Familiarity with growth marketing concepts such as: A/B Testing, Causal analysis, Incrementality, Inferential statistics, MMM etc, iOS SKAN & incoming privacy changes
Nice to have: experience with Big Data tools (Redshift/Spark/Airflow), experiment design, predictive modeling, log analysis, AI, or experience in tech or startup environments
Accountable: You take ownership of your responsibilities, demonstrating trustworthiness and self-discipline. You are consistent in your work, transparent in your actions, and communicate effectively. You follow through on commi