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Committees may include topics such as AI/machine learning, ethics, natural language processing, data definitions, data governance, genomic/pathology/radiology and other specialized clinical data systems, Epic, internal and external data reuse, learning health systems and translational science.
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As a Lead, Machine Learning Engineer, you will partner with Data Scientists, Data Engineers, Data Analysts and other professionals to implement machine learning models that will deliver stability, producibility, scalability and integration with other products and services.
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As a Machine Learning Engineer, you will partner with Data Scientists, Data Engineers, Data Analysts and other professionals. 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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Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or a related field. AI and Machine Learning: Utilize state-of-the-art AI and machine learning techniques, including natural language processing (NLP), to train the chatbot for accurate and effective communication.
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The candidate should have subject matter expertise in designing and implementing machine learning pipelines including a deep understanding of core ML frameworks such as PyTorch, TensorFlow or Scikit-learn and 3rd party ML platforms from Palantir, Dataiku, DataRobot, Alteryx and other vendors.
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You have familiarity with analytics like machine learning, natural language processing, or data visualization, particularly for creating tools that scale complex analytics workflows for less technical end users.
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Rockstar Games is on the lookout for a passionate Machine Learning Engineer with strong software development skills who possess es a passion for both games and big data. We collaborate as a global team to develop cutting-edge data pipelines, data products, data models, reports, analyses, and machine learning applications.
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Proficiency in Databricks for distributed data processing, analytics, and machine learning on big data. Proven experience as a Data Engineer with a strong emphasis on data virtualization, SQL programming, DevOps practices, Python, and Databricks.
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We offer an array of services including Core Business Application Development, Artificial Intelligence & Machine Learning, Big Data & Analytics, Visualization & Business Intelligence, Robotic Process Automation, Cloud Adoption, Mobility, Digital Adoption, Agile & DevOps, Quality Assurance & Test Automation.
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On the Data Science team, we’re looking for someone who is comfortable working on a variety of ad auction and placement optimization problems, using experimentation to improve our ads systems, and helping to lead our team in balancing monetization and quality of experience considerations across our streaming service.
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Experience with data modeling, data prep and machine learning tools like Alteryx, RapidMinder, RStudio and Tableau Prep. Experience with statistical and mathematical modeling, artificial intelligence and machine learning software and methods.
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Leverage software engineering, machine learning, data science and data engineering techniques, sourcing and using a wide range of data types as you go, to enhance our platform's capabilities and deliver innovative solutions to our customers.
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Experience in mathematics (statistics, linear algebra, differential calculus); data visualization (Tableau, Power BI, Qlikview); programming (SQL, Python, R, Java); data analysis (feature engineering, data wrangling, EDA) and machine learning (classification, regression, reinforcement learning, deep learning, clustering, dimensionality reduction.
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You enjoy collaborative, interdisciplinary approaches to data analysis and prioritize creating workable solutions in context over building the latest cutting-edge black box machine learning models.
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The Manager, Data Science will play a critical role in driving broad impact at MongoDB through aligning the team's technical capabilities with appropriate business contexts, working directly with stakeholders to connect what needs to be impacted with how data science and machine learning can provide that impact.
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data science machine learning jobs Company: Two Sigma in New York
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