Own experimentation end-to-end — design, execute, and analyze A/B tests and other experiments; define statistical significance frameworks
Drive causal inference work — lead analyses that go beyond correlation to understand the mechanisms behind product and customer outcomes
Serve as the analytics escalation point — be the go-to resource across the org when problems require deeper statistical rigor
Build and maintain methodological standards — document and review statistical methods used across the team; ensure analytical quality and reproducibility
Produce research — author internal research papers, benchmark studies, and methodology documentation; contribute to external-facing analyses (e.g., vertical benchmarking, state of AI)
Support ad-hoc deep-dives — respond to data requests from RevOps, MSS, Operations, and leadership with fast turnaround and clear narrative

Strong SQL and Python skills — you write production-quality queries and analytical scripts
Deep statistics background — hypothesis testing, confidence intervals, power analysis, causal inference
Extensive experience designing and operating experimentation frameworks at scale
Strong analytical and problem-solving abilities, with experience in data preprocessing, feature engineering, and model evaluation
Business acumen — you translate analytical findings into clear, actionable narratives for non-technical stakeholders
Excellent communication and narrative crafting skills, with the ability to explain complex methods to product, sales, and executive audiences
Experience working with LLM or AI product data is a strong plus
Familiarity with supervised learning techniques (e.g., regression, classification, gradient boosting) for predictive analytics use cases
Exposure to unsupervised learning methods (e.g., clustering, dimensionality reduction) for customer segmentation or behavioral analysis
Some experience working alongside or supporting ML model deployment — understanding inference pipelines, feature stores, or model monitoring
Comfort reading and interpreting NLP/ML research papers to stay current on methodological advances relevant to our data
Experience with BI/visualization tools (e.g., Looker, Omni, Tableau)

Unique opportunity to join on the ground floor of a fast-moving startup building at the center of AI
Tackle challenging and abstract problems while disrupting the $300BN legacy martech industry
Join an experienced high-performing team where you will have immediate ownership and impact
Experience a true meritocracy with significant career growth upside as the business scales

Senior Data Scientist, Analytics

Key skills