Data Scientist - Analytics

AppLovin is seeking a Data Scientist – Analytics to join their team, bridging engineering and business functions. This role involves working with petabyte-scale datasets from their ad and app ecosystem, analyzing high-velocity data streams from millions of daily active users. Responsibilities include developing analytics tools, monitoring systems, and reporting pipelines to enhance visibility into product health, business performance, and model outcomes. The Data Scientist will partner with research scientists, engineers, and business stakeholders to uncover insights, diagnose issues, and identify growth opportunities, ideal for someone early in their data science career.

Must Have

• Build and maintain dashboards, monitoring systems, and automated reporting.
• Develop scalable analytics pipelines to surface key metrics and detect anomalies.
• Define and refine KPIs using hypothesis-driven analysis.
• Analyze large datasets to identify trends and diagnose performance changes.
• Conduct exploratory analysis, root-cause investigations, and deep dives.
• Support engineering and research science teams in evaluating model performance.
• Assist in designing A/B tests, computing key metrics, and interpreting results.
• Apply basic statistical reasoning (variance, confidence intervals, significance testing).
• Partner with engineering to integrate new data sources and refine data structures.
• Work with product and business teams to understand analytical needs and translate them into actionable solutions.
• Bachelor’s degree in Data Science, Statistics, Computer Science, Mathematics, Economics, Engineering, or another quantitative discipline.
• Basic understanding of core statistical concepts and introductory modeling techniques.
• 0–3 years of experience in data analytics or data science.
• Proficiency with SQL.
• Proficiency with at least one analytical programming language (Python preferred).
• Ability to work with large datasets and translate findings into actionable recommendations.
• Ability to translate business questions into analytical frameworks and communicate insights effectively.

Good to Have

• Master’s degree in Data Science or a related quantitative discipline.
• Experience with BI tools such as Looker, Tableau, Superset, Metabase, or similar.
• Familiarity with cloud data warehouses (e.g., BigQuery, Snowflake) and workflow orchestration tools such as Airflow.
• Exposure to A/B testing, experiment design, or statistical evaluation.
• Understanding of digital advertising, performance marketing metrics, or online marketplace dynamics.
• Experience collaborating with cross-functional teams (engineering, product, business).

Perks & Benefits

• Hands-on experience with real production analytics, monitoring systems, and model evaluation.
• Opportunities to build foundational infrastructure that scales across teams.
• Exposure to high-scale data challenges and real-world ML performance considerations.
• A meaningful role in driving insights that inform product and business strategy.
• Competitive total compensation package.
• Pay for performance rewards approach.
• Equity and other forms of incentive compensation (as applicable).
• Dental, vision, and other benefits.

About AppLovin

AppLovin makes technologies that help businesses of every size connect to their ideal customers. The company provides end-to-end software and AI solutions for businesses to reach, monetize and grow their global audiences. For more information about AppLovin, visit: www.applovin.com.

To deliver on this mission, our global team is composed of team members with life experiences, backgrounds, and perspectives that mirror our developers and customers around the world. At AppLovin, we are intentional about the team and culture we are building, seeking candidates who are outstanding in their own right and also demonstrate their support of others.

Fortune recognizes AppLovin as one of the Best Workplaces in the Bay Area, and the company has been a Certified Great Place to Work for the last four years (2021-2024). Check out the rest of our awards HERE.

Position Overview

We are seeking a Data Scientist – Analytics to join our team and help bridge the gap between engineering and business functions at AppLovin. In this role, you will work with petabyte-scale datasets across our ad and app ecosystem, analyzing high-velocity data streams generated by tens of millions of daily active users. You will support the development of analytics tools, monitoring systems, and reporting pipelines that improve visibility into product health, business performance, and model outcomes. You’ll partner closely with research scientists, engineers, and business stakeholders to uncover insights, diagnose issues, and identify opportunities for growth.

This role is ideal for someone early in their data science career who enjoys solving ambiguous problems, has foundational statistical and modeling knowledge, and is excited to build impactful tools used across the organization.

Key Responsibilities

Analytics, Monitoring & Tooling

• Build and maintain dashboards, monitoring systems, and automated reporting to track product, business, and model performance.
• Develop scalable analytics pipelines to surface key metrics, detect anomalies, and support timely issue diagnosis.
• Define and refine KPIs, using structured, hypothesis-driven analysis to understand performance changes and long-term trends.

Insights Discovery & Model Evaluation

• Analyze large datasets to identify trends, diagnose performance changes, and uncover growth opportunities.
• Conduct exploratory analysis, root-cause investigations, and hypothesis-driven deep dives.
• Support engineering and research science teams in evaluating model performance, including stability, calibration, and long-term health.

Experimentation & Measurement

• Assist in designing A/B tests, computing key metrics, and interpreting results.
• Apply basic statistical reasoning (e.g., variance, confidence intervals, significance testing) to support decision-making.

Cross-Functional Collaboration

• Partner with engineering to integrate new data sources, refine data structures, and enable scalable analytics.
• Work with product and business teams to understand analytical needs and translate them into actionable solutions.

Minimum Qualifications

• Bachelor’s degree in Data Science, Statistics, Computer Science, Mathematics, Economics, Engineering, or another quantitative discipline.
• Basic understanding of core statistical concepts and introductory modeling techniques, with the ability to apply them in practical analysis
• 0–3 years of experience in data analytics or data science (internships or projects count).
• Proficiency with SQL and at least one analytical programming language (Python preferred).
• Ability to work with large datasets and translate findings into actionable recommendations.
• Ability to translate business questions into analytical frameworks and communicate insights effectively to both technical and non-technical audiences.
• Curious, proactive mindset with a desire to learn quickly and contribute meaningfully.

Preferred Qualifications

• Master’s degree in Data Science or a related quantitative discipline.
• Experience with BI tools such as Looker, Tableau, Superset, Metabase, or similar.
• Familiarity with cloud data warehouses (e.g., BigQuery, Snowflake) and workflow orchestration tools such as Airflow.
• Exposure to A/B testing, experiment design, or statistical evaluation.
• Understanding of digital advertising, performance marketing metrics, or online marketplace dynamics.
• Experience collaborating with cross-functional teams (engineering, product, business).

What You’ll Gain

• Hands-on experience with real production analytics, monitoring systems, and model evaluation.
• Opportunities to build foundational infrastructure that scales across teams.
• Exposure to high-scale data challenges and real-world ML performance considerations.
• A meaningful role in driving insights that inform product and business strategy.