JOB DESCRIPTION: Position is based in Charlotte, NC, some teleworking may be permitted. Travel to Lowe's offices may be required. Mines and extracts data, applying statistics and algorithms to derive insights for Lowe's and Lowe's Digital, supporting an automated insights generation framework for Lowe's business partners to interpret data effectively. Provides actionable insights through data science on Personalization, Search & Navigation, SEO & Promotions, Supply Chain, Services, and other company priorities, tracking Lowe's success through dashboard reports that measure financial results, customer satisfaction, and engagement metrics. Conducts deep statistical analysis, including predictive and prescriptive modeling, to provide a competitive advantage at Lowe's while maintaining expert-level knowledge on industry trends, emerging technologies, and new methodologies. Leads automation and analytical projects, collaborating across functions in Lowe's and Lowe's Digital, influencing and defining appropriate methodologies for team members while driving innovation in data science applications. Translates or provides guidance to junior-level scientists to convert business requirements into analytical approaches, asking the right questions to understand the problem, validating with stakeholders, and helping define the analytic approach to solving business problems. Identifies data sources, methods, parameters, and procedures to be used, clarifies expectations with stakeholders, plans resources accordingly, and leverages statistical techniques and tools to analyze data as per project plans. Communicates with stakeholders to provide updates, manage scope, and prepare final recommendations, ensuring solutions are best-in-class, implementable, and scalable within the business while adhering to enterprise project management practices. Leads execution of projects by participating in formal and informal training, staying updated on techniques, technology, industry trends, best practices, and emerging methodologies, and identifying value gaps and opportunities for process enhancements or efficiencies while integrating requirements with current systems and business processes. JOB REQUIREMENTS: Job requires a Bachelor's Degree in Mathematics, Statistics, Computer Science, Data Science, or a related field AND 6 years of experience in any job title/occupation involving analytics or a related field OR Master's Degree in Mathematics, Statistics, Computer Science, Data Science, or a related field AND 2 years of experience in any job title/occupation involving analytics or a related field OR PhD in Mathematics, Statistics, Computer Science, Data Science, or a related field. *Employer will accept single degree or combination of degrees, diplomas and/or professional experience equivalent to a Bachelor's degree. Experience and skills can be gained concurrently during degree pursuit or through any combination of academic coursework or work experience. Must have prior experience in: • Optimizing large-scale data processing workflows and executing complex queries on massive datasets using big data technologies like Google BigQuery, Apache Hadoop, and Apache Spark for efficient distributed computing and data analysis; • Deploying and maintaining machine learning models (collaborative filtering, deep learning) in production using cloud and AI platforms, ensuring scalability and efficiency in recommendation and personalization systems; • Performing large-scale data processing and executing complex queries on massive datasets, applying NLP-based machine learning models for social media analysis and classification; • Conducting spatio-temporal data analysis, hypothesis testing, and statistical correlation studies to detect large-scale behavioral patterns and identify anomalies in real-world applications like voter registration and traffic analysis; • Utilizing NLP, recommendation systems, topic modeling, and advanced data visualization to support decision-making for government agencies, research institutions, and large organizations; • Developing anomaly detection and predictive modeling techniques using SARIMA, VAR, LSTM, and CARBayes to analyze voter registration behavior and detect irregularities; and • Designing and deploying deep neural networks for climate change trend prediction, integrating geospatial analysis with large-scale Twitter and weather datasets.