Senior Data Scientist

We do. We can’t cram it all in here, but you’ll start noticing it from the first interview.

Even our candidate experience is different. And when you get an offer from us (and accept it), you get way more than a paycheck. You get a personal BetterUp Coach, a development plan, a trained and coached manager, the most amazing team you’ve ever met (yes, each with their own personal BetterUp Coach), and most importantly, work that matters.

This makes for a remarkably focused and fulfilling work experience. Frankly, it’s not for everyone. But for people with fire in their belly, it’s a game-changing, career-defining, soul-lifting move.

If that sounds exciting—and the job description below feels like a fit—we really should start talking.

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  Connect data across product, partner, and business systems, building the metrics and reporting that show how our work translates into value for our enterprise customers

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  Design and maintain data models and governed metric definitions, so the same numbers show up consistently across internal analysis, customer-facing reporting, and AI-powered tools

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  Partner with engineering to make sure the data we collect supports reliable measurement

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  Design and analyze experiments, applying causal inference methods to measure the impact of product and business changes

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  Build predictive models for problems like engagement, retention, and customer health, and put them into use across the business

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  Build systems to evaluate AI models and tools, measuring quality, safety, and consistency over time and combining automated metrics with human review

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  Run deep dives into why metrics move, and turn the findings into clear recommendations for teams across the company and leadership

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  Build with AI as part of your daily work, including agents, LLM-assisted analysis, and internal tools that help the team move faster

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  Take on projects across different areas of the business, such as product, sales, marketing, and finance, as new needs come up

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  Mentor other analysts and data scientists, and help shape how the team works

• 5+ years in data science or analytics, ideally including B2B SaaS or enterprise products

• Strong SQL and Python, plus experience with modern data tooling such as dbt, a cloud data warehouse (e.g., Snowflake, BigQuery, or Databricks), and a semantic or metrics layer

• Hands-on experience with data modeling and defining metrics that other teams depend on

• Solid experimentation and causal inference skills, including experiment design and power analysis

• Experience building and deploying predictive models, with a pragmatic approach to matching model complexity to the problem

• Experience evaluating ML or LLM-powered systems

• Deep fluency with AI tools and agentic coding workflows (e.g., Claude Code, Cursor), and a desire to help the team build and scale AI-native ways of working

• The ability to explain complex results clearly to both technical and non-technical audiences

• An owner’s mindset and comfort with ambiguity, especially in 0-to-1 work where deciding what to measure is part of the job

• Experience with NLP or analyzing unstructured text data

• Familiarity with LLM evaluation methods such as LLM-as-a-judge, golden datasets, and human review loops

• Experience with privacy-preserving data practices, such as de-identification

• Experience with behavioral or product analytics tools (e.g., Amplitude)

Our team thrives at the intersection of human expertise and AI capability. As an AI-forward company, adaptation and continuous learning are part of our daily work. We’re looking for teammates who are excited to evolve alongside technology – people who experiment boldly, share their discoveries openly, and help define best practices for AI-augmented work. These professionals thoughtfully integrate AI into their work to deliver exceptional results while maintaining the human judgment and creativity that drives real innovation. During our interview process, you’ll have opportunities to showcase how you harness AI to learn, iterate, and amplify your impact.

As a Senior Data Scientist, you’ll:

• Architect domain-level AI reinvention: identify the highest-leverage AI opportunities in how we measure and act on data, secure the resources to test them, and install repeatable mechanisms that lock in proven gains across several teams

• Build scalable AI-powered systems, from evaluation frameworks to agents and internal tools, that change how teams across the company get and use data

• Lead the evaluation and integration of emerging AI technologies into our product and analytics roadmap

We encourage all candidates to share examples of how they’ve used AI tools in their work, whether that’s agentic coding, LLM-assisted analysis, or building evaluation systems. We view AI fluency as a complement to craft, not a replacement for it.

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