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We are interested in a variety of topics including data visualization and interactivity, applied machine learning and AI, AI bias and trust, big graphs, natural language processing, data mining, big data management, and heterogenous data analytics.
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Risk modeling, credit reporting, marketing data, identity protection, HR compliance, employment verification, ACA compliance, technology, fraud prevention, artificial intelligence, machine learning, financial literacy, blockchain, cloud-based platforms, big data, trended data, data mining, cybersecurity, financial services, fintech, data analytics, cloud, and talent solutions.
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Knowledge of Machine Learning, Data Mining, Statistics, Applied Mathematics, or a related field. Under general direction, you will develop models using Machine Learning, Deep Learning, and other similar technologies to predict and analyze data on hardware and software systems within a large server infrastructure to prevent outages and pinpoint errors.
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MS in Computer Science, Information systems, or Computer engineering, Systems Engineering with relevant experience in Text Mining / Natural Language Processing (NLP) tools, Data sciences, Big Data and algorithms.
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6 years' experience with statistical or machine learning experience in marketing, credit risk, or financial, analytics domains. Advanced knowledge of machine learning & feature engineering techniques.
$120,500 - $150,314 a yearExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
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Responsibilities include delivering projects on time and within scope with an in-depth knowledge of big data and cutting edge data mining techniques as well as the use of predictive, classification, machine learning and alternate analytic algorithms for modeling and segmentation.
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R, SAS, Python), has proficiency in statistical theory and underlying mathematical distributions, and expertise in querying relational databases with SQL. They have experience with of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, and can demonstrate real-world application of these techniques.
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Machine learning mining and analysis of unstructured job description and talent data to support skills and capability gap analysis. Lead Data Scientists typically leverage and implement pre-defined analytics patterns and infrastructure on projects that are moderately complex, requiring working knowledge of a more limited set of machine learning or advanced modeling approaches.
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The CO+I Infrastructure, Planning and Acquisitions (IPA) Long-Range Planning Data Science team delivers Microsoft’s Long Range Infrastructure plan using state of the art econometric/machine learning (ML) models, risk simulations and business intelligence.
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Ability to develop predictive and prescriptive models on large scale datasets to address various business problems through leveraging advanced statistical modeling, machine learning, or data mining techniques.
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Serve as an expert consultant regarding advanced data mining and predictive modeling methods, as well as application of scientific principles of knowledge discovery. Ability to independently select and apply multiple advanced data mining, statistical analysis and predictive modeling methods.
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Experience in machine learning, big data analytics, data science, and cloud computing is a plus. Qualified candidates need to be passionate about the Machine Learning and Artificial Intelligence space, will excel in problem-solving and combine an advanced business or technical degree with consulting or product management experience and have a record of successful delivery of complex, multi-faceted projects.
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2-4 years work experience in data mining, statistical analysis, auditing, and/or forecasting. Also ensures that all reporting and analytical responsibilities are completed competently in a timely manner, continually seeks out opportunities to learn new and hone existing technical skills (e.g. writing SQL/code, statistics, machine learning, etc.
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Advanced competence in machine learning principles and techniques. Practical knowledge of advanced statistical techniques, predictive modeling, time series forecasting, and techniques such as random forest, GBM, neural networks, SVMs, ensemble models and text mining.
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Experience in data mining and understanding of Machine Learning or operations research. This position works with a team responsible for the research and implementation of predictive requirements by leveraging industry standard machine learning and data visualization tools to draw insights that empower confident decisions and product creation.
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machine learning data mining jobs in Atlanta, GA
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