Senior Data Scientist - Experimentation - Data Pipeline

As a Senior Data Scientist at Lowes, your primary responsibility will be to build and maintain a best-in-class experimentation platform/program supporting the growing suite of eCommerce products. You will play a crucial role in driving data-driven decision-making, collaborating with various teams, mentoring junior data scientists, and fostering a culture of experimentation within the organization. Key Responsibilities: - Design, develop, and maintain robust data pipelines to ensure efficient and accurate data flow from various sources to the data warehouse. - Support the design and execution of A/B tests, multivariate experiments, and randomized controlled trials (RCTs) to assess the impact of product changes, marketing campaigns, and customer experiences. - Conduct advanced statistical analysis to derive actionable insights from experimentation results and develop models to predict customer behavior and optimize key business metrics. - Stay updated with the latest advancements in data science, statistics, and experimentation methodologies and propose innovative approaches to enhance the experimentation framework. - Lead or participate in research to explore new ways of measuring and optimizing the customer journey in a retail/e-commerce setting. Qualification Required: - Ph.D. or master's degree in data science, Statistics, Mathematics, Computer Science, Economics, or a related field. - 5+ years of professional experience in data science, with at least 2 years focused on experimentation, A/B testing, and causal inference in a retail or e-commerce environment. - Advanced knowledge of statistical methodologies for experiment design, analysis, and causal inference. - Expertise in analytics/data software/tools such as Python, R, SQL, and experience with machine learning frameworks (e.g., TensorFlow, scikit-learn). - Strong communication skills to explain complex technical concepts to non-technical stakeholders and executive leadership. - Familiarity with e-commerce and retail metrics and experience working in an agile environment collaborating with cross-functional teams.,