Customer Data Scientist in London

Amplitude 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.

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.

As a Customer Data Scientist, you will combine deep experimentation expertise, applied statistics, and customer-facing technical consulting to help some of the world's most sophisticated product and engineering organisations evaluate, adopt, and scale modern experimentation programs. This is a highly strategic and technical role that partners closely with Sales, Solutions Engineering, Product, and Engineering teams. You will serve as the trusted expert on experimentation methodology, statistical rigor, and experimentation infrastructure, helping customers solve complex challenges while influencing the future direction of the Amplitude and Statsig platforms.

As a Customer Data Scientist, you will:

• Serve as the primary experimentation expert throughout customer evaluations, guiding technical discussions from discovery through proof of concept.
• Partner directly with data scientists, engineers, and technical leaders to advise on experiment design, statistical methodology, measurement frameworks, and experimentation architecture.
• Help customers build scalable and trustworthy experimentation programs by educating teams on best practices in experimentation, metric development, variance reduction, and results interpretation.
• Collaborate closely with Account Executives, Solutions Engineers, Product Managers, and Engineers to accelerate customer success and bring valuable field insights back into product development.
• Create repeatable frameworks, technical content, and enablement materials that strengthen experimentation expertise across customers and internal teams.

You’ll be a great addition to the team if you have:

• Built, scaled, or supported experimentation programs within a product-led technology company and understand both the technical and organizational challenges involved.
• Experience working with experimentation platforms such as Statsig, Eppo, Optimizely, LaunchDarkly, or similar technologies.
• Comfort engaging with highly technical audiences and can effectively communicate complex statistical concepts to data scientists, engineers, executives, and business stakeholders.
• Enjoy translating technical depth into practical business outcomes and helping organizations make better product decisions through experimentation.
• Experience influencing product strategy, technical roadmaps, or best practices based on customer needs and market feedback.

At a minimum, you need to have:

• 5+ years of experience in Data Science, Experimentation, Analytics, Applied Statistics, or a related field with a strong foundation in experimental design and causal inference.
• Hands-on experience designing, running, and analyzing A/B tests and applying advanced experimentation methodologies, including variance reduction, holdouts, sequential testing, or related techniques.
• Strong proficiency in SQL and Python and experience working with cloud data warehouses such as Snowflake, BigQuery, or Redshift.
• Experience using Python or R for statistical analysis, experimentation, and data modelling.
• Experience working directly with customers, stakeholders, or cross-functional partners to solve complex technical challenges and communicate sophisticated concepts effectively.
• Willingness and ability to travel approximately 10-25% of the time to meet with customers, support strategic engagements, and participate in team and industry events.