Product Data Analyst, Mobile App User Acquisition
StackAdapt’s Advertising Technology team is looking for a highly analytical and results-oriented Product Data Analyst to drive product and performance insights for our Mobile App User Acquisition program.
In this role, you will work closely with Product, Machine Learning, Business Intelligence, Data Engineering and business teams to define performance metrics, analyze campaign and product trends and translate complex data into actionable recommendations.
The primary focus of the role is product analytics, but we are looking for someone who can go beyond one-off analysis. Candidates with experience in analytics engineering or data engineering will be strongly preferred, particularly those who can build reliable datasets, data pipelines, dashboards and automated analytical workflows.
The ideal candidate has experience working with mobile app advertising, performance marketing or another data-intensive product environment. They should be comfortable working across structured and unstructured data sources and independently taking an analytical problem from initial question through data sourcing, analysis, visualization and recommendation.
We are also looking for someone with an AI-first mindset. Candidates who have experience using AI to accelerate analysis, automate repetitive workflows or build internal agents and reusable skills will be given preference.
What You'll Be Doing:
Analyze historical and real-time mobile user acquisition campaign data to identify trends, measure performance and uncover optimization opportunities
Define, establish and refine the core metrics used to evaluate mobile UA campaign and product performance
Partner with Product and Machine Learning teams to analyze targeting, bidding, attribution and optimization performance
Conduct deep-dive analysis into campaign delivery, conversion funnels, user quality, attribution and return on advertising spend
Build and maintain Tableau dashboards for performance monitoring, troubleshooting and product analysis
Create dashboards and reporting structures that allow Product, Engineering, Sales and Account Management teams to independently investigate performance
Lead weekly performance reviews and communicate key findings, risks and recommendations to stakeholders
Prepare quarterly business reviews and leadership updates covering performance trends, product opportunities and areas requiring investment
Work with Data Engineering, BI and Analytics teams to design scalable datasets and reporting solutions
Build or maintain Apache Airflow pipelines that consolidate data from multiple internal and external systems
Work with Snowflake, MySQL, APIs, logs, event-level data and other structured or unstructured data sources
Develop reusable data models and curated datasets that support product analytics, experimentation and operational reporting
Identify gaps in data quality, event instrumentation and reporting and partner with Engineering teams to address them
Support product experiments by defining success metrics, evaluating results and communicating recommendations
Automate repetitive reporting, investigation and analysis workflows using AI and other modern tools
Build internal AI agents, reusable skills or analytical tools that improve data discovery, troubleshooting and team productivity
What You'll Bring to the Table
Bachelor’s degree in Data Science, Business Analytics, Statistics, Computer Science, Engineering or a related field
3 or more years of experience in product analytics, data analytics, business intelligence or a related role
Strong SQL skills and experience querying large, complex datasets
Experience defining product or business metrics and converting ambiguous questions into structured analytical approaches
Experience building dashboards and data visualizations in Tableau, Looker, Power BI or a similar platform
Experience working with a cloud data warehouse such as Snowflake
Experience working with relational databases such as MySQL
Ability to independently investigate data issues, identify root causes and translate findings into clear recommendations
Strong communication and presentation skills, with the ability to explain complex analysis to both technical and non-technical audiences
Strong attention to data quality, metric consistency and analytical accuracy
Ability to collaborate across Product, Engineering, Machine Learning, BI and business teams
Preferred Qualifications
Experience in analytics engineering or data engineering
Hands-on experience building or maintaining pipelines using Apache Airflow
Experience building reusable data models, analytical tables or curated datasets
Experience with Python for data analysis, automation or pipeline development
Advanced experience building interactive Tableau dashboards for monitoring and troubleshooting
Experience with ThoughtSpot or another self-service analytics platform
Experience integrating data from APIs, event streams, logs and unstructured data sources
Experience working with Mobile Measurement Partners such as AppsFlyer, Adjust, Singular or Kochava
Understanding of mobile UA and performance marketing metrics, including CPI, IPM, click-to-install rate, ROAS, retention and lifetime value
Familiarity with mobile attribution models, view-through attribution, click-through attribution and privacy-focused measurement frameworks
Experience supporting machine learning models, experimentation or model-performance monitoring
Experience working in advertising technology, mobile user acquisition, performance marketing or another high-volume data environment
Experience using AI tools to accelerate analytics, data engineering, documentation or troubleshooting
Experience building AI agents, reusable skills, MCP-based tools or AI-powered analytical workflows
The compensation range listed for this role reflects the expected base salary for candidates located in the posting country based on a global rate. It is informed by market data and the approved budget for this position. StackAdapt maintains different compensation ranges for roles across other countries and regions, and final offers will be aligned to the candidate’s current location. We do not ask candidates about current or prior salary history, and we will not use such information, if volunteered, in setting an offer.
This range represents base salary only. Depending on the role, candidates may also be eligible for additional compensation such as annual bonuses, commissions, equity awards, and a comprehensive benefits package.
Factors Influencing Final Compensation:
The final compensation offer will be determined by a variety of factors, which may include, but are not limited to: the candidate's specific experience, technical skills, knowledge, abilities, and relevant education, licensure, and certifications.
Other business factors, such as organizational needs and budget alignment, may also be considered in the final offer.
Base Salary Band
$76,000—$104,500 CAD