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Lead a team of geographically dispersed professionals who will have responsibilities for prototyping and deploying solutions for the enterprise; Areas of expertise will include applied mathematics & statistics, machine learning operations, data engineering, software development, modelling & simulations.
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Familiar with PySpark and data processing libraries, machine learning frameworks (like Tensorflow, Keras or PyTorch), and other machine learning libraries. Familiar with Machine Learning life cycle, with knowledge of feature stores, MLflow, model registries, model deployment, model serving, and model monitoring.
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The Technology organization works to influence WMG's strategy and optimize day-to-day operations through data, insights, workflow, and machine learning, including generative AI. This position sits within the Technology organization, working closely with colleagues across WMG's recorded music and songwriting/publishing businesses.
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A baccalaureate degree from a regionally accredited college/university, including 16 semester hours (24 quarter hours) of biological science (with one semester in microbiology), 16 semester hours (24 quarter hours) of chemistry, one semester (one quarter) of mathematics, -and- one year of full time acceptable clinical laboratory experience in Blood Banking, Chemistry, Hematology, Microbiology, Immunology and/or Clinical Microscopy within the last ten years.
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Basic to substantial experience in one or more of the following commercial/open-source data discovery/analysis platforms: RStudio, Spark, KNIME, RapidMiner, Alteryx, Dataiku, H2O, SAS Enterprise Miner (SAS EM) and/or SAS Visual Data Mining and Machine Learning, Microsoft AzureML, IBM Watson Studio or SPSS Modeler, Amazon SageMaker, Google Cloud ML, SAP Predictive Analytics.
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The Biocomputational Engineering Degree is offered at the Universities at Shady Grove campus, located in Rockville, MD. The BCE degree differs from the bioengineering program in that it offers a multidisciplinary curriculum that includes statistics, data analysis, data visualization, machine learning, and programming in addition to the fundamentals of physics, chemistry, and biology.
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Role / team focus areas could include supporting machine learning, deep learning, or quant initiatives across the enterprise. At least 6 months of experience or academic work using machine learning techniques.
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Collect and analyze data using statistical and Artificial Intelligence /machine learning algorithmsSupervise and assist undergraduate students working on research projects and act as a liaison/mediator between undergraduate students and the faculty researcher.
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Should have led AI/ML projects in current role and should have the experience in designing, developing, and implementing machine learning models and algorithms. You will iterate on improvement rapidly with a mindset for failing fast and learning continuously from data.
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Experience with applied machine learning (tree-based methods, ensemble methods, neural networks/deep learning) The Data Scientist is responsible for using advanced statistical, algorithmic, machine learning, data mining and visualization techniques to help advance and complete client projects.
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The Opportunity As a Computer Scientist/Engineer on the Fraud Team, you will be at the forefront of developing and executing an innovative strategy utilizing Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), Large Language Models (LLM), and Multi-Agent Systems to combat a variety of fraudulent activities.
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Our high-performing team works with clients to implement the full spectrum of data analytics and data science, ranging from data architecture design, data engineering and querying, data visualization and dashboarding, predictive analytics, machine learning, and artificial intelligence.
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Serve as a trusted advisor to decision-makers, offering consultative insights on how the Nvidia DGX AI platform and machine learning can be applied to their biological data challenges.
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Technical Proficiency: Expertise in Python, machine learning tools (Hadoop, TensorFlow, Apache Spark), and deep learning frameworks. Your innovative approach will harness machine learning and artificial intelligence to deliver impactful solutions, enabling customers to make informed, data-driven decisions through prototypes and scalable production systems.
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Examples will include techniques such as machine learning (ML) supervised and unsupervised learning, regression, neural networks and deep learning, natural language processing, etc.
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machine learning applied mathematics jobs Title: research intern Company: Burlington Stores in Washington, DC
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