Qualtrics

Staff Data Scientist, Strategic Insights

Seattle, Washington, United StatesFull-TimeStaffAI / Data Science

Skills

Python SQL Pandas Scikit-learn A/B testing Ownership dbt Amplitude

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How You’ll Find Success

Strategic Research Drives Decisions: Your models and insights are cited in product roadmap discussions, GTM strategy sessions, and executive reviews. Leaders say "the data shows..." and reference your work.
Cross-Functional Influence: Product and GTM stakeholders seek you out for partnership on strategic questions. You translate complex analyses into clear recommendations that drive action.
Research Portfolio Management: You maintain a portfolio of 2-3 concurrent research initiatives, balancing quick wins with deeper multi-quarter investigations. You navigate competing stakeholder asks and synthesize them into coherent research plans.
Methodological Leadership: You raise the bar for how we think about usage-to-outcome modeling. The team learns from your approaches to causal inference, predictive modeling, and working with messy behavioral data.
AI-First Innovation: Qualtrics is investing in its data science and AI tool stack for our product innovation, which you’ll leverage to accelerate insight generation while maintaining statistical rigor.

How You’ll Grow

Strategic Scope: You'll own research that influences company-level strategy, giving you visibility with Product and GTM leadership and exposure to board-level discussions.
Technical Leadership Track: This role positions you for either technical leadership (principal data scientist) or people leadership (manager/director) based on your interests. The soft skills required here, including stakeholder management, ambiguity navigation, executive communication, are foundational for either path.
Cross-Functional Fluency: You'll develop deep expertise in both product analytics and revenue analytics, a rare combination that's highly valued in B2B SaaS companies.

Things You’ll Do

Own the Strategic Research Agenda: Build and maintain a portfolio of research initiatives investigating usage patterns that drive business outcomes. Navigate ambiguous or competing executive asks and synthesize them into clear research plans. Define what "good enough" looks like for each question, balancing rigor with actionability.
Model Usage to Business Outcome Relationships: Develop predictive models for renewal, expansion, and NRR based on product usage patterns. Quantify the business impact of usage improvements (e.g., "reaching X stage in Y days improves renewal odds by Z%").
Evaluate GTM Plays and Product Investments: Use casual inference methods to assess whether customer success plays or marketing campaigns are having their intended effects on usage and outcomes. Help product leaders understand the ROI of investments in specific customer journeys or features.
Translate Complex Findings into Executive Narratives: Create compelling presentations that connect statistical findings to business strategy. Write clear, actionable recommendations that non-technical stakeholders can act on. Present confidently to senior leadership across Product, GTM, and executive teams.
Collaborate Across the Data Organization: Partner with Analytics Engineering to access and shape foundational datasets. Work with product data scientists to understand product instrumentation and context. Contribute methodological expertise to the broader team's capabilities.

What We’re Looking For On Your Resume

Master's or PhD in Statistics, Economics, Computer Science, Data Science or related quantitative field preferred. Strong fundamentals in statistical inference and probability theory are more important than knowing every technique.
8+ years in data science or analytics roles, with strong experience in B2B SaaS environments (or fast-paced consulting/finance with B2B software exposure). You've spent significant time working with product usage data and business outcomes.
Experience building models connecting product behavior to revenue outcomes (renewal, expansion, NRR, churn). You've worked with messy, real-world B2B data across multiple entities (users, accounts, licenses). You've presented findings to executives that influenced product or GTM strategy.
Strong proficiency in predictive modeling for business outcomes (regression, survival analysis). Applied understanding of causal inference methods (difference-in-differences, regression discontinuity). Skilled at feature engineering from behavioral data and interpreting model outputs for business insights (feature importance, effect sizes, interaction effects).You know when fancy methods matter and when simpler approaches are more effective.
Expert in SQL for behavioral analysis (event streams, cohort analysis, user journeys). Strong Python skills for modeling and data manipulation (pandas, scikit-learn, statsmodels). Comfortable with product analytics data structures (event-based data, user properties, cohorts). Familiar with modern AI-assisted tools and interested in leveraging them for productivity.
Deep understanding of B2B SaaS business models (ARR, NRR, expansion, renewal mechanics). Experience navigating account-level vs. user-level behavior, multiple stakeholders, and long customer journeys. You speak both "product" and "revenue" languages fluently.
Exceptional written and verbal communication skills with executive presence. Proven ability to translate complex statistical findings into strategic recommendations. Track record of influencing product or GTM strategy through data insights. Comfortable presenting to senior leadership and defending your methodology.

What You Should Know About This Team

The PXE Data Science & Analytics Team has 3 specialized pillars: Data Science, Analytics, and Analytics Engineering. You'll be part of the Data Science pillar but work independently on strategic research while embedded data scientists focus on product unit partnerships and experimentation.
We're investing heavily in becoming an AI-first team. This means building exceptional foundational datasets that AI tools can leverage, adopting AI-assisted workflows that amplify our impact, and experimenting with novel AI capabilities for analytics. We believe AI makes strategic research and domain expertise more valuable, not less.
You'll report directly to the head of PXE Data Science & Analytics and work as a peer to other senior data scientists. Your stakeholders will span Product leadership (PM, UX, UX Research) and GTM leadership (Customer Success, Marketing).
The team built Customer Maturity (a top strategic KPI), established Golden Paths to measure critical user journeys, and built our product analytics instance from scratch to hundreds of monthly active users. Your research will build on this foundation to connect these usage metrics to business outcomes.
We value practical impact over theoretical perfection, cross-functional collaboration, and clear communication. We use modern tools (dbt, Amplitude, Python/R, SageMaker, AI-assisted coding) and maintain high standards for reproducible research.

Our Team’s Favorite Perks and Benefits

Qualtrics Experience Bonus: Experiences you might not otherwise have
Career Action Planning: Personalized career planning inside and outside Qualtrics
Wellness: Comprehensive benefits including wellness reimbursement and mental health support
For full-time positions, this pay range is for base per year; however, base pay offered within this range may vary depending on location, job-related knowledge, education, skills, and experience. A sign-on bonus and restricted stock units may be included in an employment offer. Full-time employees are eligible for medical, dental, vision, life and disability, 401(k) with match, paid time off, a wellness reimbursement, mental health benefits, and an experience bonus. For a detailed look at our benefits, visit Qualtrics US Benefits.