Senior Data Scientist

Design and analyze experiments, including A/B tests and observational studies, to measure business impact and support decision-making. Apply causal inference methodologies to evaluate outcomes and identify performance improvement opportunities. Develop, validate, and deploy machine learning models for prediction, classification, and analytical use cases. Apply statistical methods to quantify uncertainty, evaluate results, and ensure analytical rigor. Partner with engineering and business teams to define metrics, establish measurement frameworks, and improve data collection processes. Evaluate AI and LLM-based solutions using structured testing methodologies, performance metrics, and analytical frameworks. Communicate findings and recommendations through compelling visualizations, presentations, and data-driven storytelling. Drive adoption of advanced analytics, experimentation, and machine learning bestpractices across the organization. Bachelor's Degree in Computer Science, Information Technology (IT), or related field AND 5+ years of technical support, technical consulting, data science, analytics, or information technology experience o OR 7+ years of years of technical support, technical consulting, data science, analytics, or information technology experience Deep expertise in causal inference — experimental design and observational causal methods. Statistical foundation — hypothesis testing, regression, Bayesian and frequentist methods, uncertainty quantification. Solid machine learning skills — feature engineering, model selection, evaluation, and validation. Experience evaluating LLMs and/or AI agents — designing offline/online evaluations, defining quality metrics, and measuring model behavior. Data storytelling — crafting compelling data stories through enhanced visualizations in Python (e.g., matplotlib, seaborn, plotly) or other tools. Proficiency in Python or R and SQL.