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The Data Scientist has familiarity with industry best practices for software/hardware optimization when processing large data sets and offers experience in the following required task areas: experience with machine learning, statistical modeling, time-series forecasting, and/or geospatial analytics; experience with Hadoop, Spark, or other parallel storage/computing processes is a plus.
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We apply advanced technologies such as Digital Signal Processing, Analytics, Machine Learning, Artificial Intelligence, and Cloud computing to solve our customer and mission challenges. Explore new machine learning and artificial intelligence approaches for automated object detection, feature extraction/target state estimation, multi-source data fusion, and much more.
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Certifications and specialization in IT Ops, Infrastructure, APM, Data Engineering, Machine Learning, Data Infrastructure. Thousands of organizations worldwide, including Barclays, Cisco, eBay, Fairfax, ING, Goldman Sachs, Microsoft, The Mayo Clinic, NASA, The New York Times, Wikipedia, and Verizon, use Elastic to power mission-critical systems.
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Bachelor’s degree in computer science, Engineering, or Mathematics, Applied Mathematics, Statistics, Applied Statistics, Machine Learning, Data Science, or related field and. Collaborate with data scientists on using data science and machine learning algorithms in areas such as natural language processing, graph analytics, computer vision, and anomaly detection, in accordance with industry and academic best practices.
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Experience with big data analytics, machine learning, artificial intelligence, or anomaly. Infrastructure Support (IS) certification, including CEH, CySA+, GICSP, SSCP, CHFI, Experience with DevSecOps, CI and CD, IaC and CaC, IT Infrastructure Library, and IT.
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Advanced knowledge of cloud computing technologies such as: Apache Spark, Azure Data Factory, Azure DevOps, Azure ML (Machine Learning), Hadoop, Microsoft Azure, Databricks, AWS, Google Cloud.
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System engineering, Cloud computing, Cyber security, Data science and analytics, Artificial Intelligence (AI), Machine Learning (ML), Application development, Network operations, Secure communications, DevSecOps.
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Provide independent data science, machine learning, and analytical insights using member, financial, and organizational data to support mission critical decision making for Compliance-Complaints.
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Knowledge of cloud computing technologies such as: Apache Spark, Azure Data Factory, Azure DevOps, Azure ML (Machine Learning), Hadoop, Microsoft Azure, Databricks, AWS, Google Cloud. Experience in using two or more of the following modeling types to solve business problems: classification, regression, time series, clustering, text analytics, survival, association, optimization, reinforcement learning.
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Hands-on experience with technology such as sensors and signal processing, machine vision and machine learning, and internet-of-things type technology. Knowledge of autonomous sensor deployment and AI-driven machine vision.
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Experience with big data analytics, machine learning, artificial intelligence, or anomaly detection. Experience with DevSecOps, CI/CD, IaC and CaC, IT Infrastructure Library, and IT Service Management.
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Data science, machine learning, optimization models, PhD 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.
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Learning & Development - Programs offering certification and tuition support, digital on-demand learning courses, mentorship, and skill development paths. Demonstrated proficiency in the design and implementation of modern data architectures and concepts such as cloud services (e.g., AWS, Azure, GCP), real-time data distribution (e.g., Kafka, Kinesis,DataFlow, Airflow), NoSQL (e.g., MongoDB, DynamoDB, HBase, CosmosDB) and modern data warehouse tools including Snowflake and DataBricks.
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With expertise in rapid prototyping, manufacturing, artificial intelligence/machine learning and autonomy, we transition advanced technologies and integrated systems to U.S. Government customers including all branches of the US military, DARPA and other research laboratories, and the Intelligence Community.
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Our application development domain includes embedded control, digital signal processing, machine learning, enterprise applications, middleware and user interface development. Our application development domain includes embedded control, digital signal processing, machine learning, enterprise applications, middleware and user interface development.
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machine learning jobs Company: The Realreal in Herndon, VA
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