Job Description Collect and extract large sets of structured and unstructured data from various sources such as databases, APIs, and web scraping. Develop predictive models using machine learning algorithms to forecast trends and future outcomes. Develop and integrate AI agents to automate data collection, preprocessing, and analysis tasks, enhancing efficiency and scalability. Utilize generative AI models to create synthetic data, augment data sets, and generate insights. Deploy models, systems, and AI agents developed; monitor and maintain them to ensure they are working effectively. Document processes and methodologies to ensure that work is reproducible and can be audited. Work with cross-functional teams such as product managers, software engineers, and business analysts to identify business problems and develop solutions. Explain complex technical concepts to non-technical stakeholders in a clear and concise manner. Qualifications Master's degree in a quantitative field such as Data Science, Computer Science, Statistics, Mathematics, Physics, or Engineering. Knowledge of the AI/ML lifecycle management and tools, including EDA, Modeling, Integration/Deployment, Data/Model drift detection, Model retraining, etc. Familiarity with core techniques in statistical and machine learning, e.g., regularized regression, time series analysis, decision trees, boosting algorithms, neural networks, clustering, and collaborative filtering. Experience working with structured, semi-structured, and unstructured data sources. Knowledge in web crawling, natural language processing, and visualization. Familiar with collaborative solutions, model & code versioning (Github), solution packaging (Docker), model deployment (Dataiku). Proficient in programming languages such as Python, R, and SQL (for data manipulation, cleaning, and analysis), Tableau, PowerBI or Spotfire, NumPy, Pandas, and Matplotlib for visualization. Experience in developing and deploying generative AI models and large language models (LLMs). Skills in Robotic Process Automation (RPA) and automation software development. Knowledge of UI and UX design principles to enhance user interaction and experience in data-driven applications. Ability to define problems, generate hypotheses, develop and test solutions, and effectively communicate complex technical concepts to non-technical stakeholders. Attention to detail. Ability to collaborate effectively with others to achieve project goals. Additional Information Western Digital thrives on the power and potential of diversity.
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