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A minimum of two years of experience in implementing or supporting major indirect tax technology solutions such as ONESOURCE, Vertex, Avalara and similar for North American and/or global organizations.
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Experience in the Design and implementation of AI/ML models and solutions using Google Cloud Platform technologies, including but not limited to Vertex AI , BigQuery, AI Platform, TensorFlow Extended (TFX), Dataflow, and Compute Engine.
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5+ years' experience in implementation of tax related solutions in SAP including but not limited to tax requirements for direct tax such as corporate income tax, operational transfer pricing, state income taxation and indirect (transaction tax) solutions including but not limited to using native SAP functionality, ONESOURCE Indirect Determination, Vertex, Avalara, Sovos (Taxware.
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Delivery experience in Data Engineering with Google Cloud Platform including Big Query, Dataflow, Cloud Data Fusion, Cloud Composer, Dataproc, Cloud Pubsub, Cloud Function etc. Experience in Natural language processing (NLP), Prompt engineering, Embedding, Vector DB.
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We are seeking an experienced Project Manager to lead the Indirect Tax Workstream as part of a Tax engine implementation project (Vertex) in conjunction with our ERP upgrade to S/4HANA (project Magellan.
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Provide excellent client facing service to multi-national companies with global indirect tax technology issues, including transaction analysis, supply chain, business expansion, and mergers and acquisition.
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Possess deep functional and technical understanding of the Machine Learning technologies (Googles Cloud Platform, custom and COTS-embedded) and provide prescriptive guidance on how these are leveraged across the Fuse landscape.
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Familiarity with cloud computing platforms (e.g., AWS, GCP, Azure) and experience in deploying machine learning models in a cloud environment using platforms such as AWS SageMaker and GCP Vertex AI.
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Interact and support indirect tax discussions with cross functional teams such as Tax, IT, Purchasing, Sales, and Master Data. Understanding of key indirect tax processes and data drivers while possessing some industry background including retail, financial services, manufacturing and telecommunications.
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Must have good understanding of AI platform provisioned by Microsoft Azure, Google Vertex or Amazon. Data & AI, Data Cloud using Snowflake, Databricks, Azure Synapse, GCP – GBQ or AWS Redshift.
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Implement, train, and fine-tune LLM and GPT-like models on large-scale datasets to ensure optimal performance and accuracy. Encourages informed risk-taking and acts as a catalyst for innovation at Fuse; generates practical, sustainable and creative options to solve problems and create business opportunities, while maximizing existing resources.
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Fuse’s innovation culture and modern product development teams power the evolution of our commercial products and spark the creation of new businesses and products. Ensure effective designs and quality deliverables in the ML space by designing and developing machine learning and deep learning systems, running machine learning tests and experiments, implementing appropriate ML algorithms.
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Designing and developing machine learning and deep learning solutions and systems. Design thinking drives our teams to imagine and invent the next horizon. Propose, own initiatives and demonstrate though leadership that improve the efficiency and productivity of the data science Center of Excellence.
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SAP, Onesource Indirect Tax (Sabrix), Taxware, or Vertex systems experience preferred. Join our winning team as an Indirect Tax Manager in Clayton, MO. In your role, you will handle sophisticated multi-state and multi-national tax issues, focusing on indirect tax matters.
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The Vertex Companies, LLC (VERTEX) is a leading multidisciplinary engineering and consulting firm that provides environmental solutions, engineering design, forensic consulting, construction management, and claims & dispute resolution services to municipalities, state agencies (DOTs), architects, developers, real estate owners, property managers, and commercial clients.
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