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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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Much of our work contributes to innovative research in the fields of sensor science, signal processing, data fusion, artificial intelligence (AI), machine learning (ML), and augmented reality (AR.
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Understanding of strengths and weaknesses in application of Machine Learning and Artificial intelligence to applications in Transaction monitoring and Sanctions screening. Reviews ongoing model performance, assess overall model health within a given framework, identify potential problems and work with stakeholders to resolve issues identified.
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In our Data science track we prepare you to get job as one of the following: Python developer, a data analyst, data visualization developer, a statistician, a machine learning engineer or a data scientist.
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Demonstrated expertise in machine learning, deep learning, and NLP, with a strong portfolio in large language models like GPT-3, BERT, and RAG.Advanced proficiency in Python, with hands-on experience in ML libraries and frameworks such as TensorFlow and PyTorch.
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Using natural language processing (NLP), machine learning (ML), Generative AI, and other relevant AI technologies and platforms; Building machine learning models and systems, interpret their output, and communicate their results to internal/client teams and how those outcomes realize business value.
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4- 8 years of experience as machine learning engineer/data scientist. Experience using machine learning libraries or platforms, including Tensorflow, Caffe, Theanos, Scikit- Learn,or ML Lib for production or commercial products.
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Data Architecture & Tools: modern cloud data platforms (Snowflake, Databricks, Big Query, RedShift), data analytics tools (Tableau, Looker, Power BI), data programming models (DataFrames, pandas), and AI (Python, R, Jupyter Notebooks, data wrangling, machine learning.
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Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment. Many of the research methods we employ are analogous to, or drawn from, domains such as artificial speech recognition, brain-machine interface design, computational neuroscience, and array signal processing as used in lidar, radar, sonar, and ultrasound applications.
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Duties: Engage in model validation on quantitative models - Evaluate conceptual soundness of model specifications, reasonableness of assumptions and reliability of inputs, perform implementation testing on Wholesale and Commercial Bank models including Basel models, Machine Learning Models and CCAR Stress Testing Models.
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Provide technical vision, drive strategy around solutions, solve complex problems, and act as the technical owner across strategic efforts involving the UI/UX platform, Cloud, streaming, machine-learning and more.
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The Data & Analytics department in Legal and Compliance is responsible for designing and optimizing surveillance models, approaches and tools using advanced analytical techniques like supervised and unsupervised machine learning, Natural Language Processing (NLP) and evolving techniques like reinforcement and deep learning as well as graph analytics.
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Job Description The Dey Lab in Computational & Systems Biology program at Memorial Sloan Kettering Cancer Center is seeking postdoctoral fellow in machine learning/artificial intelligence and applied statistics to lead inter-disciplinary collaborative projects in biological sciences supervised by Dr. Dey, in collaboration with Dr. Rahul Mazumder, MIT Sloan School of Management.
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Preferred Qualifications- Previous experience or advanced coursework in data science, algorithmic engineering, or machine learning. Basic experience with versioning software such as Git.- Working knowledge of data visualization software such as Tableau, Looker, or Domo.- Fundamental knowledge of statistics with some hands-on experience in A/B testing, regression analysis, and ANOVA testing.
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This is an ideal role for someone who thrives in ambiguity and has a consistent track record of contributing to the product strategy and roadmap for a complex machine learning problem space.
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machine learning jobs Title: health in New York, Missouri-city, Missouri
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