[Hiring] Product Data Analyst @StackAdapt

Role Description

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.

Qualifications

• 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.

Benefits

• Highly competitive salary.
• Retirement/401K/Pension Savings globally.
• Competitive Paid time off packages including birthdays off!
• Access to a comprehensive mental health care program.
• Health benefits from day one of employment.
• Work from home reimbursements.
• Optional global WeWork membership for those who want a change from their home office and hubs in London and Toronto.
• Robust training and onboarding program.
• Coverage and support of personal development initiatives (conferences, courses, books, etc.).
• Access to StackAdapt programmatic courses and certifications to support continuous learning.
• An awesome parental leave program.
• A friendly, welcoming, and supportive culture.
• Our social and team events!