SummaryPosted: Dec 8, 2024Weekly Hours: 40 Role Number:200581609Imagine what you could do here. At Apple, great new ideas have a way of becoming phenomenal products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish! The AppleCare Business Insight, Operations and Systems (ACBIOS) team is seeking an innovative and passionate Support Knowledge Graph Data Scientist who is responsible for building analytical assets, and generating insights into the quality of Apple's products and software. This is an exciting opportunity to directly impact our customers' experience and support Apple products throughout their life cycle.DescriptionDescriptionThe core function of this role is to apply skills in machine learning, knowledge graphs, and software engineering, to create services that will allow a deep understanding of why customers contact Apple for support, and how to best help them. The output from this will help teams around Apple understand what product and software improvements are priorities to address. Other key functions of this role include: Collaborate with cross-functional teams to establish relationships, develop performance indicators, and communicate complex data analyses. Research, experiment, and implement new technologies and methods to combine knowledge graphs with LLMs and other technologies/techniques. Handle large, complex sets of unstructured text, and use advanced analytics to tackle challenging problems within them. Minimum QualificationsMinimum QualificationsMA or MS degree in statistical analysis, computer science, data science, ontology, knowledge graphs, applied mathematics, or related field.10+ years experience in deploying graph based data science or machine learning techniques to solve practical business problems.Outstanding written and verbal communication, with the ability to make complex data science concepts understandable to non-technical audiences.Proficiency in SQL, preferably in Snowflake. Proficiency in graph query languages.Strong programming skills in Python with experience using packages such as Pandas, NumPy, scikit-learn.Experience in quantitative data analysis, possessing a strong ability to conduct in-depth evaluations of complex issues.Have a creative approach to engineer innovative features and signals into analytical solutions, pushing the boundaries of current tools and methodologies.Experience leveraging Large Language Models (LLMs) to generate, refine, or analyze text data for practical applicationsDemonstrated experience in leading data science projects through all phases including exploratory data analysis, data quality management, modeling, tool deployment, and presentation of results.Proficiency with knowledge graph tools and frameworksExperience with data integration and entity resolution to consolidate disparate data sources into a coherent graph structureAbility to apply graph-based algorithms (e.g., pathfinding, clustering, recommendation) to extract insights or improve analytics.Key QualificationsKey QualificationsPreferred QualificationsPreferred QualificationsPhD in graph machine learning, or knowledge graph related fields.Experience building web based graph visualization and analytics tools.Experience developing methods for integrating knowledge graphs with LLMs to enrich model responses with factual accuracy and context.Experience implementing pipelines that allow LLMs to dynamically access and retrieve information from knowledge graphs for complex question-answering tasks.Education & ExperienceEducation & ExperienceAdditional RequirementsAdditional RequirementsMore

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