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Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Various market research firms, including Forrester and Gartner, have recognized our business value and leadership.
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Experience with Deep Learning methods in NLP, sentiment analysis, topic modeling, and graph theory and databases. Capgemini Government Solutions (CGS) LLC is seeking a highly motivated data scientist to develop Computer Vision and Machine Learning algorithms to build solutions.
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7+ years of experience in machine learning, deep learning, and natural language processing. Experience in ML model life cycle development experience and prefer experience to common algorithms like XGBoost, CatBoost, Deep Learning, etc.
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MiniTab, SAS, Matlab, VBA)Proficiency with any data visualization software (e.g. Tableau, Qlik, Power BI, D3, Shiny)Demonstrated experience with practical applications of advanced forecasting (e.g. time series models, ARIMA, TBATS, XGBoost) or mining large first party datasets (e.g. churn, CLV, up/cross sell, shrinkage methods, clustering, random forests) [NNs and deep/reinforcement learning familiarity is a plus, but not required]Demand Planning experience preferred.
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Strong expertise in machine learning algorithms, deep learning, and large-scale recommendation systems. Role Overview:As a Staff Machine Learning Engineer specializing in personalization, you will play a crucial role in developing models and algorithms that tailor the user experience by recommending the most relevant offers.
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Deep knowledge and hands-on expertise in predictive modeling, statistical inference, machine learning, and other advanced analytical techniques. Experience using programming and data manipulation languages (SQL, R, Python, C/C.
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Strong understanding of machine learning and deep learning concepts including transformer based GPT models. Prototype and test AI solutions using Python and Streamlit with a focus on natural language processing and text extraction from documents (PyPDF, Azure Document Intelligence.
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Deep understanding and experience with advanced analytics, Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP) or Computer Vision (at least 3 of these areas.
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In-depth knowledge of machine learning and deep learning concepts, including transformer-based GPT models. Prototype and test AI-driven solutions with a focus on NLP and document text extraction using Python, Streamlit, PyPDF, and Azure Document Intelligence.
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Proficient in Python, Pytorch, Tensorflow, Keras and Githubs with deep learning experience in RNN, CNN, NLP or imaging is a plus. - Shows proficiency in development, implementation, and rollout of statistical and deep learning tools and techniques (e.g. using R, R-shiny, Python, Julia, etc.
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Advanced knowledge in computer programming (preferably R or Python), machine learning, deep learning, natural language processing, and applied statistics is required. We are encouraging applicants with strong research background in data science, machine learning, or natural language processing with a focus on biomedical applications.
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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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Fluency in Python programming and related machine learning tools (such as NumPy, Pandas, and scikit-learn), deep learning frameworks (such as TensorFlow or PyTorch), and SQL-like query languages (such as Spark.
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This role will leverage expertise in AI engineering, natural language processing, and machine learning to design, develop, and deploy innovative solutions that capitalize on both structured and unstructured data.
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If you have knowledge, through coursework or project work, of Python, Machine Learning, Deep Learning, Mathematics, or Statistics/ Modeling, this opportunity is right for you.
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