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Must have a strong background in one or more of the following: Mathematical, Statistics, Probability, Deep Learning, Machine Learning, Natural Language Processing, Computer Vision, Recommendation Systems, Pattern Recognition, Large Scale Data Mining or Artificial Intelligence.
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Extracts and analyzes complex information from large structured and unstructured datasets using data mining and data modeling, NLP, and Machine Learning (ML). DE identifying key trends and customer behaviors that influence business decisions by building hypothesis for mining digital or live channel data in AWS and Snowflake EDL, using SQL, Python, Elasticsearch and Amazon Web Services (AWS) technologies Athena, Glue, Sage maker, Kibana, S3, Quicksight, and API Gateway.
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Proficiency in programming languages such as Python, R, or SQL. Strong knowledge of machine learning techniques, statistical analysis, and data visualization tools Tableau, Power BI). Perform data mining, statistical analysis, and predictive modeling.
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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.
$184,000 - $248,400 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Certificate in business analytics, data mining, or statistical analysis, Statistical programming languages (for example, SAS, R) Techniques: Statistical Analysis, Visualization, Optimization, Machine Learning, Big Data, Data Warehouse, NLP.
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Use analytic methods and advanced knowledge in machine learning, statistics, text mining, natural language processing, computational semantics, computer vision, and data science to develop creative solutions to complex real-world problems.
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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.
$184,000 - $248,400 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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1) Drive business impact by identifying and acquiring or mining data from multiple and diverse sources for actionable insights (including digital session web data, Salesforce and other CRM/CDP/IAM platforms, Google Analytics and Google BigQuery, etc.
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JOB SUMMARY FOR Data Modeler:This role involves applying quantitative and qualitative analysis to synthesize trends into actionable insights, delivering deep-dive analyses, and data mining using Alteryx.
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As a Machine Learning Engineer, you will work as part of a team to assist, develop, and collaborate in ML models and algorithms, specifically focusing on integrating Azure OpenAI services and Large Language Models.
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This isn't analyst work; you'll be leveraging data science methods, including AI and machine learning in an incredibly dynamic and engaging environment. Data science, machine learning, optimization models, Master's degree in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
$136,000 - $200,000 a yearFull-timeExpandApply NowActive JobUpdated 28 days ago - UpvoteDownvoteShare Job
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Stay up-to-date with the latest advancements in data science, machine learning, and related fields, and apply them to improve existing processes and methodologies. Experience with data visualization tools and techniques to effectively communicate insights and findings.
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The Computational Biology group in the Clinical Biomarkers & Diagnostics (CBD) department at is seeking a highly motivated Sr data scientist to join our team and contribute to develop machine learning modeling and prediction pipelines using multi-modal biomarker data from clinical trials.
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Extracts and analyzes complex information from large structured and unstructured datasets using data mining/modeling, Natural Language Processing (NLP), and Machine Learning (ML) techniques.
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The Research Associate Data Scientist participates in biomedical research projects using programming, data mining, statistics, machine -learning, and visualization techniques to develop, evaluate, and/or apply algorithms and software for data analysis.
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