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Amida is currently looking for a Data Scientist to join our team in Washington, DC. In this role you will work across our client engagements, providing expertise in machine learning algorithms, natural language processing (NLP), data collection, data analysis, data mapping, data profiling, data mining, data modeling, and data visualization.
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Support AAG leadership in extending and growing our machine learning, engineering and analytics capabilities. 10+ years of software engineering, analytics development or machine learning engineering experience.
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Our work combines genomics, proteomics and state-of-the-art imaging technologies with software engineering, machine learning and data science. Pioneer novel methods for multi-modal data analysis (e.g. network analysis, machine learning) and develop new data visualization solutions.
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Machine Learning Engineering - Dallas, TX (Hybrid) Clean, preprocess, and transform raw data into a suitable format for machine learning models. Collaborate with data scientists, software engineers, domain experts, and client stakeholders to understand requirements, gather feedback, and integrate machine learning solutions into larger systems or products.
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As a member of the Data Engineering team, the Machine Learning Engineer will work closely with business domain experts and Data Scientists to solve real-world oil and gas midstream problems using advanced analytics, machine learning, and artificial intelligence.
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We're on the lookout for an accomplished Staff Data Scientist to join the Data Engineering & Analytics team at StubHub. In this role, you'll play a pivotal part in crafting and deploying cutting-edge machine learning models that drive business and operational choices within StubHub's dynamic ecosystem.
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What you’ll bring to Circle: 5+ years of experience in data analysis or data science, with 3+ years focusing on machine learning problems, ideally in a relevant space (KYC, sanctions detection, anti-fraud detection, treasury management, crypto/blockchain data science.
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Utilize: Machine Learning, Data Science, Python, Data Engineering, Software Engineering, Structured Query Language (SQL). One (1) year of experience must include utilizing Machine Learning, Data Science, Python, Data Engineering, Software Engineering, Structured Query Language (SQL.
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Preferred Skills 5+ years in a data engineering role with demonstrable experience with Cognitive computing, data integration, data mining, Natural Language Processing, Hadoop platforms, and automating machine learning components.
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In this role, the Machine Learning Engineer will work with a variety of data-driven technologies, including traditional and deep learning paradigms. The Machine Learning Engineer should have a combination of generalist machine learning skills, engineering analysis skills, and the ability to quickly develop specialist capabilities where needed.
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Techniques: Statistical Analysis, Visualization, Optimization, Machine Learning, Big Data, Data Warehouse, NLP. Drive the adoption of data science-driven mechanisms and machine learning models to continuously evaluate and improve catalog data quality.
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Certificate in business analytics, data mining, or statistical analysis, Statistical programming languages (for example, SAS, R) Define business priorities across channels, 1P and Marketplace, collaborating with cross functional teams (engineering, product, data science, and operations), ensuring there is a strong roadmap.
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Our specialized data centers run computing-intensive applications powered by clean energy for: Cryptocurrency Mining Artificial Intelligence Deep Learning Machine Learning Scientific Computing Natural Language Processing Video Transcoding and more.
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Scientific background in life sciences or engineering and demonstrated expertise in one or more of the following areas: data analytics, data visualization, statistics, machine learning, predictive modeling, decision analysis under uncertainty, artificial intelligence, Python and/or R, app development, and Tableau dashboard development.
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Experience with machine learning tools such as mlFlow, Databricks AI/ML, Azure ML, AWS sagemaker, etc. Leading team in the definition of best practices & repeatable methodologies in Cloud Data Engineering, including Data Storage, ETL, Data Integration & Migration, Data Warehousing and Data Governance.
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machine learning data mining engineering jobs Title: data Company: Amazon Web Services Aws
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