Data Scientist – Analytics

Details

AppLovin is seeking a Data Scientist – Analytics to help bridge the gap between engineering and business functions. The role involves working with petabyte-scale datasets across the advertising and app ecosystem, analyzing high-velocity data streams generated by tens of millions of daily active users, and developing analytics tools, monitoring systems, and reporting pipelines. The position is suited to someone early in their data science career with foundational statistical and modeling knowledge who is interested in building impactful tools.

Responsibilities

Analytics, Monitoring, and 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 and 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 and Measurement

• Assist in designing A/B tests, computing key metrics, and interpreting results.
• Apply statistical reasoning, including variance, confidence intervals, and 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.
• Collaborate with research scientists, engineers, and business stakeholders to uncover insights, diagnose issues, and identify growth opportunities.

Requirements

• 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 and projects count.
• Proficiency with SQL and at least one analytical programming language, preferably Python.
• 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 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 such as BigQuery or Snowflake.
• Familiarity with 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 engineering, product, and business teams.

Benefits

• Competitive total compensation package with a pay-for-performance rewards approach.
• Equity eligibility.
• Medical, dental, vision, life, and disability insurance.
• 401(k) retirement plan.
• Unlimited discretionary time off.
• 10 paid holidays per year.
• 80 hours of paid sick leave.

The California base pay range is $120,000–$180,000 USD. Total compensation may vary based on market location and job-related knowledge, skills, and experience. Equity and other incentive compensation may be provided depending on the position offered. The application window is expected to close within 30 days of the posting date. AppLovin is an equal opportunity employer.