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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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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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Experience in one or more areas of quantum computing such as algorithm development, quantum error correction, NISQ/hybrid quantum algorithms, quantum machine learning, or quantum error mitigation.
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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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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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Hands-on experience with machine learning (including deep learning and reinforcement learning), and one or more of the following technical areas: large language models (LLM), generative AI, decision science, human machine teaming, cognitive science, AI testing and evaluation, multi-agent systems, knowledge-based reasoning, automated planning, semantics, and ontologies.
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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. 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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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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San Francisco, California (Hybrid On-Site): $248,700 - $283,800 for Sr. Lead Machine Learning Engineer. New York City (Hybrid On-Site): $234,700 - $267,900 for Sr. Lead Machine Learning Engineer.
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This candidate should be proficient in using BI tools such as Tableau, in addition to experience with one or more modern technologies such as relational databases, AWS, Snowflake, Python, Databricks, Git, and Machine Learning.
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Demonstrates advanced functional knowledge of data visualization libraries such as matplotlib or ggplot2; knowledge of other visualization tools such as Microsoft Power BI and Tableau. ALTA is an established leader in IT Staffing and Services, for both government and commercial enterprises across the United States, specializing in Program & Project Management, Application Development, Cybersecurity, Data & Advanced Analytics, and Agile Transformation Services.
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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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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. 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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Knowledge of AWS Cloud Administration, Terraform Infrastructure as Code, Ansible, Amazon Machine Images (AMI), AWS Secrets Manager, AWS Certificates Manager, EC2 Scripting, Lambda. Utilize Amazon Machine Images (AMIs) to streamline application instance deployment.
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Net, C#, Power BI, Machine Learning, Azure Data Factory, RedShift, UiPath, Cloud, RPA, AWS, Redshift, Python, Data Modeling, SQL, SSIS, SSAS, SSRS, Power Automate, Power Platform, AI Builder, Power Apps, Blue Prism, Automation Anywhere, UiPath Studio, Orchestrator, ERP, QuickBooks, SAP, NetSuite, Oracle, API, JSON, XML, Web Services, SOAP, Postman, Fiddler, Integration, Custom Activities, DLL, Insight, Automation Hub, Task Capture.
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machine job Title: expert Company: The Realreal in Reston, VA
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