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Salary: USD 160,000 - 225,000 / annual
BetterUp is seeking a Senior Data Scientist to shape how the company uses data to improve products and business outcomes serving employees at major global organizations. This is a builder role focused on connecting data across the business—from product usage to customer value—and creating metrics that drive decision-making across the company.
Key Responsibilities:
- Connect data across product, partner, and business systems to build metrics and reporting that demonstrate value for enterprise customers
- Design and maintain data models and governed metric definitions ensuring consistency across internal analysis, customer-facing reporting, and AI-powered tools
- Partner with engineering to ensure collected data supports reliable measurement
- Design and analyze experiments using causal inference methods to measure impact of product and business changes
- Build predictive models for engagement, retention, and customer health, and deploy them across the business
- Build systems to evaluate AI models and tools, measuring quality, safety, and consistency through automated metrics and human review
- Conduct deep dives into metric movements and translate findings into clear recommendations for teams and leadership
- Integrate AI into daily work, including agents, LLM-assisted analysis, and internal tools that accelerate team velocity
- Take on cross-functional projects across product, sales, marketing, and finance as needs arise
- Mentor other analysts and data scientists; help shape team processes
The role emphasizes AI-forward thinking, with opportunities to architect domain-level AI reinvention, build scalable AI-powered systems, and lead evaluation and integration of emerging AI technologies into the analytics roadmap.
Requirements:
- 5+ years in data science or analytics, ideally with B2B SaaS or enterprise product experience
- Strong SQL and Python proficiency
- Experience with modern data tooling: dbt, cloud data warehouse (Snowflake, BigQuery, or Databricks), semantic or metrics layer
- Hands-on data modeling and metric definition experience that other teams depend on
- Solid experimentation and causal inference skills, including experiment design and power analysis
- Experience building and deploying predictive models with pragmatic approach to model complexity
- Experience evaluating ML or LLM-powered systems
- Deep fluency with AI tools and agentic coding workflows (e.g., Claude Code, Cursor); desire to help team build AI-native ways of working
- Ability to explain complex results clearly to technical and non-technical audiences
- Owner's mindset and comfort with ambiguity, especially in 0-to-1 work where defining what to measure is part of the job
Nice to Have:
- NLP or unstructured text data analysis experience
- Familiarity with LLM evaluation methods (LLM-as-a-judge, golden datasets, human review loops)
- Privacy-preserving data practices (de-identification)
- Behavioral or product analytics tools experience (e.g., Amplitude)
