Primary Skills: ML, Python, SQL, JavaScript/HTML/CSS for frontend visualization, MLOPs Fundamentals, GenAI, Causal Inference Secondary Skills: PySpark Detailed Job Description from Hiring Manager: About the Role As a Senior Data Scientist for Walmart Global Tech, you will play a key role in driving data-driven decision-making across multiple retail domains. You will design, build, deploy, and scale machine learning and Generative AI solutions that directly impact business performance. Key Responsibilities 1. Lead the development of ML and GenAI solutions to solve business problems in retail functions. 2. Collect, validate, and synthesize large-scale datasets to support analytics and model development. 3. Apply big data analytics and data science techniques to identify trends, patterns, and anomalies, and determine additional data requirements. 4. Design, deploy, and maintain production-ready ML systems, including real-time and batch inference pipelines. 5. Collaborate with business stakeholders to communicate insights, influence strategy, and drive data-backed decisions. 6. Own the end-to-end ML lifecycle, including model training, evaluation, deployment, monitoring, and retraining. Qualifications * Bachelor's or master's degree in computer science, Statistics, Mathematics, or a related field with 5+ years of experience in data science. * Proven experience deploying and managing AI/ML models. * Hands-on experience implementing Generative AI-based solutions in production. * Experience in scheduling jobs for automated training and inference of AI/ML models using airflow or any other workflow orchestration platform. * Strong programming skills in Python and PySpark. * Proficiency in SQL, relational databases, data warehouses, and BigQuery. * Experience in building AB testing and causal inference solutions * Solid understanding of regression, classification, and unsupervised learning machine learning algorithms. * Strong experience in data collection, data cleaning, preprocessing, and feature engineering. * Proficiency in collecting data from different data sources, data cleaning, preprocessing, and feature engineering. * Strong written and verbal communication skills, with the ability to present and explain complex concepts to both technical and non-technical audiences.

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