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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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Is required (test required)Algorithmic trading experience is required (essential), whether personal or professional experience Desirable Skills: Prior experience as a Quantitative Trader/ ResearcherExperience with Machine Learning, Natural Language Processing or Deep LearningKnowledge of the DeFi and Web 3.0 ecosystem.
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Machine Learning and Deep Learning: Good understanding of: ML algorithms like linear regression, logistic regression, etc., supervised, unsupervised, and reinforcement learning, AI Frameworks like TensorFlow, PyTorch, scikit-learn etc., Neural network, NLP, computer vision, and predictive analytics.
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Required Skills : 2+ years of building out predictive models (Regression, Time Series, Natural Language Processing, Pattern Recognition, Classification, Segmentation, Deep Learning) STRONG SQL, Python.
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Basic knowledge and experience in statistical and data mining techniques such as: generalized linear model (GLM)/regression, random forest, boosting, trees, text mining, hierarchical clustering, deep learning, convolutional neural network (CNN), recurrent neural network (RNN), T-distributed Stochastic Neighbor Embedding (t-SNE), graph analysis, etc.
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Expert ability in operations research and statistical methods and techniques, including deployment analysis and resource allocation modeling, systems/operations analysis, simulation and optimization (linear and nonlinear, predictive analytics (e.g. deep learning, econometrics, time series/forecasting, vehicle routing, and related skills.
$78,721 - $150,000Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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RNN) in a work setting, not just academic projects Hands-on experience in building and deploying machine learning and statistical models using Python, PySpark, Machine Learning libraries, SQL. Experience in computing/programming skills; proficiency in Python, R, and Linux shell script.
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The Enterprise Model Platform team in the Machine Learning Experience (MLX) organization supports a hosted internal Jupyter Notebook system running critical infrastructure for modeling and exploratory analysis across Capital One. You will get an opportunity and exposure to the thousands of models being trained on the notebook platform by myriad users across Capital One and dive deep into the unique engineering challenges we have around data access, security and scale.
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Utilize programming languages like Java, Python, SQL, Node, Go, and Scala, Open Source RDBMS and NoSQL databases, Container Orchestration services including Docker and Kubernetes, and a variety of AWS tools and services.
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Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Our business value and leadership have been recognized by various market research firms, including Forrester and Gartner.
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Ability to communicate technical details to nontechnical stakeholdersStrong machine learning background in Python; experience with Spark, PyTorch or TensorFlow. Leverage computer vision, NLP, GenAI, entity resolution, Deep Learning to create the best Consumer facing menus for Merchants.
$170,600 - $255,800 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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At least 2 from the following: Statistics and Probability Theory, Regression Modelling, Clustering Methods, Deep Learning, Neural Networks, Natural Language Processing, Text Mining, Computer Vision, Image Recognition, Time Series Forecasting, Machine Learning Visualization Tools, Tree Ensembles.
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Qualified candidates will have 1-2+ years of experience including a strong background in NLP and Machine Learning or Deep Learning, as well as mastery of Python and familiarity with Tensorflow, Scitkit-learn, Pandas, etc.
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Python or related language- Experience with neural deep learning methods and machine learningPREFERRED QUALIFICATIONS- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
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Come join us We are looking for a Lead Software Engineer who has deep experience in creating the capabilities that turn data into meaningful connections and insights. Strong skills in programming languages such as Python or Java. Strong knowledge of API design and microservices architecture.
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