Lead Product Data Analyst, Mobile App User Acquisition

StackAdapt is a technology company that empowers marketers to reach, engage, and convert audiences through its AI-powered marketing platform. The Lead Product Data Analyst will drive product and performance insights for the Mobile App User Acquisition program by defining metrics, analyzing campaign and product trends, and translating data into recommendations. The role also involves building dashboards, datasets, pipelines, and AI-enabled analytical workflows in collaboration with Product, Machine Learning, Engineering, BI, and business teams.

Responsibilities

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

Preferred

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

Analytics Engineering

Data Engineering

Apache Airflow

Data Pipeline Development

Data Pipeline Maintenance

Reusable Data Modeling

Analytical Table Development

Curated Dataset Development

Python

Data Analysis

Data Automation

Interactive Tableau Dashboards

Dashboard Monitoring

Dashboard Troubleshooting

ThoughtSpot

Self-Service Analytics Platforms

API Data Integration

Event Stream Integration

Log Data Integration

Unstructured Data Integration

Mobile Measurement Partners

AppsFlyer

Adjust

Singular

Kochava

Mobile User Acquisition Metrics

Performance Marketing Metrics

Cost Per Install (CPI)

Installs Per Mille (IPM)

Click-to-Install Rate

Return on Ad Spend (ROAS)

User Retention Metrics

Lifetime Value Metrics

Mobile Attribution Models

View-Through Attribution

Click-Through Attribution

Privacy-Focused Measurement

Machine Learning Model Support

Model Performance Monitoring

Advertising Technology

Mobile User Acquisition

Performance Marketing

High-Volume Data Environments

AI Agent Development

Reusable AI Skills

MCP-Based Tool Development

AI-Powered Analytical Workflows

Benefits

Retirement/ 401K/ Pension Savings globally

Competitive Paid time off packages including birthday's 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!

Company

AI-powered programmatic advertising and marketing platform

Toronto, Ontario, CAN

https://www.stackadapt.com/

Founded in 2014

1001-5000 employees

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

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

Required skills

SQL, Product Analytics, Tableau, Snowflake, MySQL, Apache Airflow, Python, Data Visualization, Data Modeling, Data Pipelines, Mobile User Acquisition, Performance Marketing, Mobile Attribution, Machine Learning, A/B Testing, AI Agents, Stakeholder Management

Preferred skills

Experience in analytics engineering or data engineering

Experience

3+ years