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Amplitude is on a mission to help companies build better products through data. Following our acquisition of Statsig, we now offer one of the most comprehensive experimentation and product analytics platforms on the market.
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 organizations 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.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
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No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
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.
- Comfortable 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.


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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 modeling.
- Experience working directly with customers, stakeholders, or cross-functional partners to solve complex technical challenges and communicate sophisticated concepts effectively.
- Willing and able to travel approximately 10-25% of the time to meet with customers, support strategic engagements, and participate in team and industry events.
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