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Proficiency with data platform architecture, design, data dictionaries, multi-dimensional models, objects, star and snowflake schemas as well as structures for data lakes, data science, and data warehousesExtensive experience with big data technologies and cloud platforms (e.g., AWS, Azure, GCP.
$241,000Full-timeRemoteExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Candidates should be familiar with some of the following: subsurface imaging with passive seismic data, geomechanics, earthquake characterization, seismicity forecasting, seismic wave physics, big data processing, machine-learning-based processing, distributed fiber optic sensing, seismic sensors and deployment, hydraulic fracturing, and/or geothermal exploration.
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As a Data Scientist at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
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Hands-on experience with deploying models to production and building ML pipelines (Docker, CI/CD/CT) Experience with Time Series and NLP problems Solid Knowledge of Supervised and Unsupervised Machine Learning Models Knowledge of Feature Engineering, Data Wrangling/Cleaning Knowledge of Jupyter notebooks and big data environments/training (Spark, Hadoop, etc.
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Experience with data visualization tools, knowledge of data engineering, data modeling, and big data technologies. As the leader for Product Data Science, you will establish the roadmap for your team and implement projects in data science, artificial intelligence, machine learning, and product insights.
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Experience building large scale data sets in AWS, Hadoop or similar big data environments. Using your affinity for synthesizing and visualizing data, domain expertise, data mining and communication skills, you’ll ensure we’re building the best product for our current and future Pinners.
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Experience with big data technologies such as Hadoop, Spark, or cloud-based platforms like AWS, Google Cloud, or Azure. You understand the data science lifecycle and are experienced in development and implementation of advanced statistical models and machine learning algorithms.
$282,720Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Some Python development experience, including statistical analysis and data science tools. You’ll work side-by-side with a friendly but driven team of mechanical, electrical, software, and firmware engineers and data scientists that have built technologies from satellites to novel batteries and ultra-precise cooking devices to secure OS’s and industrial-scale logistics software.
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The Opportunity Adobe is looking for a Machine Learning Engineer who will apply AI and machine learning techniques to big-data problems to help Adobe better understand, lead and optimize the experience of its customers.
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We do this by providing businesses with access to world class, on-demand data science talent that helps them solve real business problems. Data Science problems are everywhere, but the talent is not.
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Adobe is looking for a Machine Learning Engineer who will apply AI and machine learning techniques to big-data problems to help Adobe better understand, lead and optimize the experience of its customers.
$219,100 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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You’ll work with a team of engineers and cross-functional partners across product, design, data science, and user research to define a product strategy and drive execution through conception, research, implementation, and maintenance.
$250,000 a yearFull-timeExpandApply NowActive JobUpdated 11 days ago - UpvoteDownvoteShare Job
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You have experience with big data ingestion, compute, and storage systems based on Spark, Kafka, Flink, and data lake and data warehouse technologies. You'll work cross-functionally with partners from the Data Science, Data Engineering, AI, Product, Go-to-Market, Legal and Finance organizations to deliver short- and long-term impact.
$250,000 a yearFull-timeExpandApply NowActive JobUpdated 2 months ago - UpvoteDownvoteShare Job
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Solid fundamentals in other computer science and computer engineering topics: algorithms and data structures, operating systems, computer architecture, etc. Prior experience in container-based deployment systems like Kubernetes is a big plus.
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Passion for big data, analytics (MMM, MTA, Experimentation), data science, and machine learning: comprehension of marketing analytics, specifically Marketing Mix Modeling, Multi-Touch Attribution (MTA), media strategy, media planning, identity resolution, data management, onboarding, remarketing, and data science is an advantage.
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data science big jobs in San Francisco, MO, Wyoming
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