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Develop solutions focused on data science and engineering using machine learning, deep learning algorithms, statistical concepts, data modeling, software development and visualizations.
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1 year of experience delivering solutions in at least two of the following: data science, data research, geospatial, finance, econometrics, cloud computing or big data and database management.
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On any given day, you might:Evaluate open-source and internally-developed modeling and analytics tools using real business dataIntegrate internal data with external data sources and APIs to discover and implement actionable insightsDesign and craft data science models to communicate solutions to customers and company leadershipWe'd love to find someone who is.
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What You'll Do Apply fundamental and advanced quantitative methods, including machine learning and statistical modeling, to solve complex business problems and enable data-driven decision-making (e.g., build statistical and machine learning models for trend analysis and forecasting to predict future business outcomes for a Fortune 100 company) Collaborate with client data science teams to enhance, scale, and operationalize existing models.
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Stay updated with the latest trends and advancements in data science, machine learning, GenAI space and cloud computing. Design and implement data-driven solutions using Microsoft Azure’s tools and services, such as Azure Machine Learning, Azure Databricks, Azure Data Factory and Azure databases or Fabric implementation.
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As the global leader in experience-centric operational analytics, Conviva has redefined big data analytics with our paradigm-shifting Time-State Analytics model. Join us to help extend our leadership position in big data streaming analytics to new audiences and markets.
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The Data Science team leads the strategy, development and integration of Machine Learning and Artificial Intelligence. Build production ready prototypes for, and iteratively develop, end-to-end data science pipelines including custom algorithms, statistical models, machine learning and artificial intelligence functions to meet end user needs.
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Proven experience with enterprise-scale technical delivery experience with AI Services including OpenAI, Schematic Kernel, AWS Bedrock, Machine Learning (or equivalent), Generative AI, LLM customization, NLP, Search, MLOps, Open-source AI frameworks, AI Infrastructure, architecture design.
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We are particularly interested in candidates in the areas of Artificial Intelligence (including Machine Learning, Natural Language Processing, Computer Vision, and Knowledge Engineering), Data Mining and Analytics, Cybersecurity, Human Centered Computing (including Information Visualization, Human Computer Interaction, Social Computing, Pervasive & Ubiquitous Computing), Network Science, Cloud Computing, and Information System Design.
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As a member of the Clinical Data Science Leadership Team, the Executive Director, Data Science is accountable for Development’s machine learning and artificial intelligence strategy, overseeing the expansion of the industry-leading Advanced Analytics organization to address the growing opportunity for value generation through the application of AI/ML, including large language models (LLMs), across Development.
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At least 6 months experience or academic work using open source programming languages for data analysis. Evaluate open-source and internally-developed modeling and analytics tools using real business data.
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Faculty research interests include algorithms and theory, AI and machine learning, bioinformatics, cyber-physical systems, computer networks, computer science education, computer vision and image processing, computational topology, data science, high performance computing, human computer interaction, open-source software, robotics and remote sensing, security and privacy, and software engineering.
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Proficiency in programming languages such as Python, R, or SQL. Strong knowledge of machine learning techniques, statistical analysis, and data visualization tools Tableau, Power BI.
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2+ years of experience with open-source research or collection of PAI sources including social media, blogs, databases, maps, videos, academic literature, news media and journals, technical publications, professional publications, economic data, demographic data, and survey research.
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Explore new machine learning and artificial intelligence approaches for automated object detection, feature extraction/target state estimation, multi-source data fusion, and much more.
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machine learning open source big data science jobs Company: Walmart
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