Senior Data Scientist
AmplitudeAmplitude is the leading AI analytics platform, helping over 4,700 customers—including Atlassian, Burger King, NBCUniversal, and Square—build better products and digital experiences. With powerful AI Agents embedded across our platform, teams can analyze, test, and optimize user experiences faster than ever. Ranked #1 across multiple categories in G2’s Winter 2026 Report, Amplitude is the best-in-class solution for product, data, and marketing teams. Learn more at amplitude.com.
As an organization, we deliver for our customers by living our values. We operate from a place of humility, take ownership of problems and successes, approach challenges with a growth mindset, and put our customers at the center of everything we do.
Amplitude’s Commitment to Diversity Equity & Inclusion (DEI): Amplitude believes that diversity enables the creation of better products, improves the ability to solve complex problems, and drives more powerful solutions. We strive to create an environment of inclusion—one focused on psychological safety, empathy, and human connection—that will allow employees of all backgrounds to thrive.
About The Role & Team
We’re looking for a Data Scientist to join the Experiment team within Amplitude. You will be part of a passionate group of product managers, engineers and designers who are working to help modern businesses transform their products through data and experimentation. As a Data Scientist, you have a unique opportunity to deeply influence the product with your knowledge and views on advanced statistical methodologies and customers who are looking to learn from an expert on experimentation best practice.
Join Amplitude and play a crucial role in shaping the future of experimentation and digital analytics. If you’re driven by innovation, strategic impact, and customer success, we’d love to hear from you!
Our ambitious machine learning for experimentation agenda includes but is not limited to:
- Causal effects modeling or heterogeneous treatment effects analysis
- Analyzing experiments that have social network effects (ex: difference in differences, Switchback, Synthetic Control)
- Time Series modeling
- Bayesian hypothesis testing
- Understanding how teams run experiments
- B2B Experimentation
- Innovating and implementing machine learning and data mining algorithms on distributed platforms to solve real-world product analytics and user behavior modeling problems.
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