Lead Data Science Analyst, GTM Strategic Analytics and Insights

## Responsibilities - Build and maintain advanced predictive and time-series models: design, train, deploy, and monitor models across use cases such as demand forecasting, capacity planning, deal scoring, and customer propensity; incorporate seasonality, exogenous drivers, and backtesting frameworks to ensure accuracy and robustness - Apply statistical rigor: lead deep-dive analyses leveraging regression, causal inference, hypothesis testing, correlation analysis, and other statistical methods to surface actionable signals from complex, large-scale datasets - Develop AI/LLM-powered solutions: architect and implement AI-first analyses and tooling using large language models, prompt engineering, retrieval-augmented generation (RAG), and related techniques to automate insight generation, surface qualitative signals at scale, and augment team capabilities - Own forecasting and decision systems: own end-to-end forecasting and operational decision systems, including time-series demand forecasting, capacity planning models (e.g., Erlang-based staffing), and production pipelines that power GTM and Support planning workflows; ensure reliability, scalability, and business adoption of outputs - Drive customer intelligence: develop and maintain prospect, deal health, archetype, and capacity models that inform GTM strategy, planning, and growth initiatives - Define the measurement framework: identify, create, and steward benchmarks and metrics that meaningfully represent growth, engagement, and success outcomes - Communicate with impact: distill complex analyses into clear, cohesive narratives with executive-ready materials that drive decisions at the senior leadership level - Collaborate cross-functionally: partner with Systems & Engineering, GTM Operations, Rev Ops & Planning, Product, Business Intelligence, Data Science, and Finance to ensure analytical solutions are integrated, scalable, and trusted ## Requirements - 6+ years of professional experience in an advanced analytics or data science role; SaaS experience strongly preferred - Deep expertise in statistical inference and modeling, including supervised techniques (regression, classification, gradient boosting, decision trees) and unsupervised techniques (clustering, PCA, anomaly detection, topic modeling) - Hands-on experience designing and deploying AI/LLM-based solutions, including prompt engineering, fine-tuning, RAG pipelines, or LLM-integrated analytics workflows; you approach new problems with an AI-first mindset - Familiarity and experience with distributed coding projects, including using Git for code management - Advanced proficiency in Python (pandas, numpy, scikit-learn, xgboost, statsmodels, and LLM/AI libraries such as LangChain, OpenAI SDK, or HuggingFace) and SQL; working knowledge ## Nice to Have - None specified ## Benefits - At Klaviyo, we value the unique backgrounds, experiences and perspectives each Klaviyo (we call ourselves Klaviyos) brings to our workplace each and every day. We believe everyone deserves a fair shot at success and appreciate the experiences each person brings beyond the traditional job requirements. If you’re a close but not exact match with the description, we hope you’ll still consider applying. Want to learn more about life at Klaviyo? Visit klaviyo.com/careers to see how we empower creators to own their own destiny.