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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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Experience leveraging complex data to drive business decisions, hands-on experience in data science methodologies (predictive analytics, machine learning, patient level data triggers) using R, Python, Databricks and deep knowledge of Qlik, PowerBI, Tableau for visualization.
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Experience in statistical programming language (e.g., Python), applied machine learning techniques, and using OSS frameworks (e.g., TensorFlow, PyTorch). Experience designing and deploying with one or more of the following ML frameworks: TensorFlow, PyTorch, JAX, Spark ML, etc.
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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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As a Quantum Computing Research Scientist Vice President within the Global Technology Applied Research (GTAR) center at JPMorgan Chase & Co., you will have the opportunity to advance the theoretical understanding of quantum algorithms for optimization, stochastic modelling, numerical analysis, machine learning and financial use cases.
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Advanced degree preferred, with 5+ years of experience in Applied Econometrics, Statistics, Data Mining, Machine Learning, Analytics, Mathematics, Operations Research, Industrial Engineering, or related field preferred.
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Experienced in one or more major machine learning frameworks: Tensorflow, Pytorch, JAX, Keras, MXNet, Scikit-Learn. Applied AI ML opportunities are available at the VP level for our Quant AI team within the Machine Learning Center of Excellence.
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As an Associate in our Risk Analytics and Modeling team, you’ll have the opportunity to apply your quantitative, modeling and analytical skills in a real world environment to develop or validate statistical, financial engineering, and AI/machine learning models in the areas of credit risk, market risk, assets and liabilities management, fraud detection, anti money laundering and other functional modeling and analytics area.
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5 years of industry experience at a leading tech or trading company working on the core Machine Learning Research team. An elite quantitative trading firm, that has invested 100s of millions into machine learning research to build one of the world's most advanced prediction machines - is actively looking for a highly skilled Deep learning specialist to join their business and become a major player in the direction of their ML research.
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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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A Ph. D. in Applied Mathematics, Machine Learning, Computational Biology or Computer Science with emphasis on applications in molecular biology and/or computational pathology (required.
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Utilize cutting-edge machine learning approaches and construct sophisticated machine learning models including deep learning architectures on big data platforms.
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Experience in Data science and Machine learning using Python, R, Java, C#, Spark, AutoML, TensorFlow, Amazon AML, Microsoft machine learning studio, PyTorch, IBM Watson and any graph DB.
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Requirements: Requires a Master’s in Statistics, Computer Science, Data Science, Machine Learning, Applied Math, Operations Research, Economics, or a related field plus two (2) years of experience as a Data Scientist, Data Engineer, or other occupation/position/job title involving research and data analysis.
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Drive innovation in the Data Science and Technology practice, focusing on generative AI and machine learning. Proficient in machine learning frameworks like TensorFlow and PyTorch.
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tensorflow machine learning applied science hands on jobs Company: Dice in Newark, NJ
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