Principal Data Scientist (AI)

Location: Hybrid in the Greater Seattle Area, with three days per week in the Seattle office (Monday, Tuesday, and Thursday)

Base salary: $200,000–$220,000 per year, plus meaningful equity.

Company

Venture-backed company building an AI platform for human skills and measurable communication improvement, serving enterprise customers and learners in more than 150 countries.

What you will do

• Own the measurement strategy and define metrics for learners' measurable skills development.
• Design and run the experimentation program, including A/B tests, holdouts, power analysis, sequential testing, guardrail metrics, and rigorous LLM evaluation.
• Build the data foundation, including pipelines, a semantic layer, dashboards, and analytical models for internal decisions and customer-facing analytics.
• Partner with product, design, and engineering to turn ambiguous questions into analyses that influence product direction.
• Develop models for scoring, skill progression, benchmarking, churn prediction, and expansion prediction from communication signals.
• Advise customers, executives, and the board by translating analysis into clear recommendations and defensible decisions.

Requirements

• 8+ years of experience in data science, product analytics, or a closely related field, including experience as the most senior data professional for a product or business line.
• Deep expertise in SQL and Python, with experience shipping production-grade analytical code.
• Experience building and operating an experimentation program rather than running only individual tests.
• Experience evaluating LLM or other generative systems, including evaluation sets, rubrics, and quality measurement without clean ground truth.
• Fluency with modern data stacks such as dbt, Snowflake, and BigQuery, plus BI tools such as Looker, Mode, or Hex.
• Ability to work onsite in the Seattle office three days per week and be based in the Greater Seattle Area.

Nice to have

• Experience with speech analytics, NLP, or conversational AI.
• Experience with embedded or customer-facing analytics.
• Early-stage startup experience.

Culture & Benefits

• Mission-driven work focused on helping people improve communication skills.
• High-autonomy ownership of the data function with executive visibility.
• Collaborative and inclusive startup environment with room to build a future data team.
• Competitive compensation and meaningful equity.
• Flexible work environment.