Job at a glance
What You'll Do Avalara is looking for a senior People Analytics Data Scientist who will architect advanced analytics and AI-powered solutions that shape our global workforce strategy. In this role, you'll go far beyond traditional reporting and apply machine learning, causal inference, and AI-augmented listening tools to answer the most complex questions about how people work, grow, and thrive at Avalara.
What sets this role apart is true end-to-end ownership: from building data foundations and designing AI-assisted listening programs to delivering predictive insights that drive executive decisions. You'll operate at the intersection of people science, AI, and strategy and partner with senior People, Finance, and business leaders in a rigorous, evidence-based global SaaS environment. This role reports to the Head of People Analytics.
This role is not eligible for visa sponsorship #LI-Remote What Your Responsibilities Will Be AI-Powered People Analytics Design and deploy machine learning and predictive models, including natural language processing (NLP), sentiment analysis, and generative AI applications to surface workforce signals at scale. Leverage AI tools to automate data pipelines, accelerate hypothesis testing, and enhance the speed and accuracy of insight delivery.
Serve as a practitioner and advocate for AI-first analytics, helping the People team adopt new AI capabilities and embedding them into everyday workflows. Employee Listening & Workforce Intelligence Lead the analytics approach for employee listening programs, including engagement surveys, pulse checks, lifecycle touchpoints, and always-on feedback channels—translating signal into actionable intelligence.
Build NLP and text analytics models to mine open-ended survey responses, exit interviews, and qualitative feedback at scale, identifying themes, sentiment trends, and early attrition signals. Design listening architectures that integrate structured (HRIS, performance) and unstructured (survey, verbatim, Slack/Teams signals) data to produce a holistic view of the employee experience. Partner with People leaders to close the loop and translate listening insights into targeted interventions and measuring their impact over time.
Advanced Statistical Modeling & Experimentation Design and execute rigorous analyses using experimental design, causal inference, and quasi-experimental methods (e.g., difference-in-differences, propensity score matching) to evaluate the effectiveness of people programs. Build, validate, and refine predictive and explanatory models using R, Python, and SQL against large, complex HR and business datasets.
Manage the full analytical lifecycle: data preparation, feature engineering, model evaluation, and stakeholder-ready insight delivery. Strategic Partnership & Influence Collaborate directly with senior People, Finance, and business leaders to frame hypotheses, ensure analytical rigor, and champion data-driven decision-making. Communicate complex analytical findings—including AI model outputs and listening program results—in clear, compelling narratives for non-technical executive audiences.
Deliver multiple high-impact analytical workstreams in parallel, balancing rigor, speed, and business relevance. What You'll Need to be Successful 5+ years applying advanced analytics methods (experimental design, quasi-experimental approaches, predictive modeling) to people or business decisions. Proficiency in Python and SQL; experience with R is a plus. Hands-on experience building, validating, and iterating on statistical or ML models using large, complex datasets.
Experience with employee listening platforms (e.g., Qualtrics, Glint, Culture Amp, Medallia) and the ability to design analytics strategies around them. Demonstrated use of NLP, text analytics, or sentiment analysis to extract insight from unstructured employee feedback data. Familiarity with AI/ML tools and frameworks—including LLMs and generative AI—and a track record of applying them