About AppLovinAppLovin makes technologies that help businesses of every size connect to their ideal customers. The company provides end-to-end advertising solutions for businesses to reach, monetize and grow their global audiences. For more information about AppLovin, visit: ;br>
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.
AppLovin is seeking a
Measurement Data Scientist to join our Product Partnerships & Measurement team. This role is ideal for someone who is deeply curious about data and metrics-someone who doesn't just analyze numbers, but strives to understand the nuances, assumptions, and limitations behind them. You'll play a key role in helping us triangulate across multiple sources of truth-platform data, 3rd-party measurement (MMM, MTA, incrementality, post purchase survey, etc), and internal attribution systems-to uncover actionable insights that drive smarter business and marketing decisions.
You'll collaborate closely with the Partnerships, Marketing Science, and Business Development teams to interpret results, refine methodologies, and translate insights into strategies that drive impact for AppLovin, our partners, and advertisers.
Key Responsibilities- Investigate performance metrics across platform and 3rd-party measurement systems to identify inconsistencies, uncover insights, and drive clarity.
- Analyze data using SQL and Python (pandas, numpy, sklearn, matplotlib) to extract trends and inform business decisions.
- Synthesize complex data into clear, actionable insights and communicate them effectively across technical and non-technical audiences.
- Develop a strong understanding of advertising and commerce ecosystems, including conversion tracking, attribution, media mix modeling and incrementality.
- Partner with internal and external stakeholders to design and evaluate incrementality tests, and to interpret results and insights from MMM, MTA, brand lift, post-purchase studies, and other measurement frameworks.
- Ask critical questions, challenge assumptions, and continuously refine the metrics and frameworks used for evaluating performance and provide guidance to advertisers on their learning agendas.
- Build tracking frameworks to monitor test performance and campaign outcomes; follow up and follow through with advertisers and partners to ensure best-practice setup, proper tracking, and adoption of key learnings.
- Collaborate cross-functionally to translate analytical findings into business strategies that improve campaign effectiveness and advertiser ROI.
- Experience in advertising, digital marketing, or eCommerce analytics.
Minimum Qualifications- Strong SQL skills and experience with large-scale data manipulation.
- Thorough understanding of data structures.
- Proficiency with Python for data analysis (pandas, numpy, sklearn, matplotlib)
- Significant experience in data analysis in an online environment, with direct exposure to scoping and executing analytical projects end-to-end
- Strong communication skills and ability to translate analytical findings into clear business recommendations.
- Highly curious and detail-oriented, with an investigative mindset and comfort working with messy or incomplete data.
- Demonstrated ability to manage competing priorities and deliver results in a fast-paced environment.
- Collaborative and flexible team player who takes initiative and drives continuous improvement.
Preferred Qualifications- Experience in advertising, digital marketing, or eCommerce analytics.
- Experience with industry-standard measurement methodologies, including CLS, RCTs, attribution modeling, incrementality testing, and GeoLift.
- Demonstrated ability to apply AI techniques to marketing measurement challenges.
AppLovin provides a competitive total compensation package with a pay for performance rewards approach. Total compensation at AppLovin is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Depending on the position offered, equity, and other forms of incentive compensation (as applicable) may be provided as part of a total compensation package, in addition to dental, vision, and other benefits.
Other Types of Pay: Equity eligible
Health Insurance: Medical, Dental, Vision, Life, Disability
Retirement Benefits: 401(k) Retirement Plan
Paid Time Off: Unlimited Discretionary Time Off
Paid Holidays: 10 paid holidays per year
Paid Sick Leave: 80 hours per year
Method of Application: Apply online
Application Window: The application window is expected to close within 30 days of the posting date.
All questions or concerns about this posting should be directed to
CA Base Pay Range
$98,000-$148,000 USD
AppLovin is proud to be an equal opportunity employer that is committed to inclusion and diversity. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status, or other legally protected characteristics. Learn more about EEO rights as an applicant here.
If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send us a request at
AppLovin will consider for employment all qualified applicants with criminal histories in a manner consistent with applicable law. If you're applying for a position in California, learn more here.
To support an efficient and fair hiring process, we may use technology-assisted tools, including artificial intelligence (AI), to help identify and evaluate candidates. All hiring decisions are ultimately made by human reviewers.
Please read our Global Applicant Privacy Notice to learn more about how AppLovin processes your personal information.
Never miss an opportunity! Create an alert based on the job you applied for.