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Preferred indirect tax (transaction tax) experience with using native Oracle product functionality, ONESOURCE Indirect Determination, Vertex, Avalara, Sovos (Taxware) Preferred indirect tax (transaction tax) experience with using native Oracle product functionality, ONESOURCE Indirect Determination, Vertex, Avalara, Sovos (Taxware.
$108,430 - $246,870 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Participate in technical planning & requirements gathering phases including Design, code, test, troubleshoot, and document engineering software applications to include strong Python development experience, particularly with the LangChain library and GenAI environment(s), any of Azure OpenAI, AWS Bedrock, Google Vertex, Google Gemini.
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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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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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Strong preference toward direct software experience with Vertex, Avalara, Alteryx, and SAP. The Indirect Tax Manager is a valuable contributor to Swire Coca-Cola and the Finance team. Strong preference toward direct software experience with Vertex, Avalara, Alteryx, and SAP.
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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. Possess deep functional and technical understanding of the Machine Learning technologies (Google's Cloud Platform, custom and COTS-embedded) and provide prescriptive guidance on how these are leveraged across the Fuse landscape.
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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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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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In-depth understanding of Google Cloud ecosystem for Data Engineering & MLOps - cloud composer, dataproc, dataproc serverless, big query, cloudrun, vertex, vertex pipelines, GKE. Working knowledge of Client frameworks, such as Vertex, Kubeflow, MLflow, CloudRun etc.
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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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MD, PharmD by training and Healthcare informatics experience preferred. Strong understanding of machine learning principles, including supervised and unsupervised learning, deep learning, and reinforcement learning.
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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.
$108,430 - $246,870 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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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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They will use relevant statistical techniques, machine learning models and artificial intelligence algorithms to analyze data, design data models and derive insights to influence actions that maximize business value and effectiveness for the commercial technology segments.
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