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The Department of Information Sciences and Technology (IST) has 44 full-time faculty members with research foci in cybersecurity, data mining and machine learning, natural language processing, human-centered computing, and computing and engineering education.
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Bachelor’s degree plus at least 7 years in a data engineering role including ETL development, database development, data integration, data mining, big data. The Senior Data Engineer will work with our data warehousing team to transform transactional data into datasets that are consumable by a variety of consumers, for reporting and analytics.
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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.
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Bottom of Form Conducts data analytics, data engineering, data mining, exploratory analysis, predictive analysis, and statistical analysis, and uses scientific techniques to correlate data into graphical, written, visual and verbal narrative products, enabling more infom1ed analytic decisions.
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Experience with cognitive computing, data integration, data mining, Natural Language Processing, Hadoop platforms, or automating machine learning components. Experience with data mining using methods and tools and with performing ETL activities using Apache NiFi.
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Leverage advanced machine learning techniques, including deep learning and reinforcement learning, to improve fraud detection and prevention models while adhering to privacy regulations.
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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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Excellent technical credentials in various subfields relevant to AI (e.g., Data Science, Data Engineering, Machine Learning, Deep Learning, Generative AI, Computer Science.
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2+ years of experience with OpenSearch, Kafka, Vue.js and some exposure to Machine Learning. Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, mentoring other members of the engineering community.
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Apply engineering principles, industry standards, company process, and knowledge of vehicle dynamics, aerodynamics, propulsion, classical/modern control, and estimation theory to perform tasks to advanced program/project goals.
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Experience developing and delivering technology in at least two of the following areas: data analytics, machine learning, data visualization, geospatial analysis, web services, or database development.
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The ideal candidate will have a strong background in data engineering, with expertise in Databricks, DevOps tools (Jenkins/Terraform), and data modeling concepts (3NF, Dimensional, Data Vault.
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Experience with Cloud Computing Technologies/Amazon Web Services (AWS). The Cyber Security Engineer must display an excellent understanding of technology and utilization of Firewalls (Security Groups), VPNs, Data Loss Prevention (DPS), IDS/IPS, Web–Proxy, Security tools, and Security Audits.
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Demonstrable expertise in an area of data science or analytics (e.g. machine learning, deep learning, NLP, computer vision, predictive modeling and forecasting, statistics.
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Data Center Technician Job Description - Run Ops (Layer 1) Responsibilities: Cabling & Termination ● The Fiber Technician will mount and install racks, patch panels, fiber optic and hardware. Data Center Technician Job Description - Run Ops (Layer 1) Responsibilities: Cabling & Termination ● The Fiber Technician will mount and install racks, patch panels, fiber optic and hardware.
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machine learning data mining engineering jobs Title: engineer data Company: Amazon Web Services Aws in Reston, VA
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