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Experience with big data technologies and tools (, Databricks, Hadoop, Spark) is a plus. The Opportunity As a Computer Scientist/Engineer on the Fraud Team, you will be at the forefront of developing and executing an innovative strategy utilizing Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), Large Language Models (LLM), and Multi-Agent Systems to combat a variety of fraudulent activities.
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Proficient understanding of relational (e.g. Oracle, SQL Server, PostgreSQL) and Big Data distributed structures (Hadoop/Spark) in order to source data effectively. The Data Scientist is responsible for using advanced statistical, algorithmic, machine learning, data mining and visualization techniques to help advance and complete client projects.
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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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You can use Spot Instances for various stateless, fault-tolerant, or flexible applications such as big data, containerized workloads, CI/CD, web servers, high-performance computing (HPC), and test & development workloads.
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Graduate Big Data Analytics Natural Language Processing Machine Learning Data Mining Cybersecurity Cyber-Human Systems. 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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Preferred Qualifications for the Cyber Engineer:·Experience with cloud security, including AWS, Azure, or GCP.·Knowledge of big data analytics, machine learning, and anomaly detection.
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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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Building and applying data analysis algorithms (data mining, statistics, machine learning, natural language processing, sentiment analysis, text mining, etc.) You’ll spend most of your time working with a wide variety of clients to deliver the latest data science and big data technologies and practices to design, build and maintain scalable and robust solutions that unify, enrich and analyze data from multiple sources.
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Data Architecture & Tools: modern cloud data platforms (Snowflake, Databricks, Big Query, RedShift), data analytics tools (Tableau, Looker, Power BI), data programming models (DataFrames, pandas), and AI (Python, R, Jupyter Notebooks, data wrangling, machine learning.
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Senior Software Engineer , you will be responsible for working on projects that support and extend the full stack of the TRSS solutions suite to deliver global data using advanced search, big data ingestion and analytical processing using tools like MongoDB, Elastic, and Kafka as well as building leading-edge web applications.
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Experience in AI, Python programming and one of the following Deep Learning frameworks, PyTorch, MXNet, TensorFlow, Keras, and big data technologies like Hive, PySpark, Synapse, and Databricks.
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Our capabilities range from C5ISR, AI and Big Data, cyber operations and synthetic training environments to fleet sustainment, environmental remediation and the largest family of unmanned underwater vehicles in every class.
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As a Data Scientist on the deployment & platform side of the team, you’ll be at the forefront helping us to usher in the next wave of disruption by using the latest technology to deploy, optimize and modernize model pipelines and execution platforms that enable machine learning models to provide powerful insights about our portfolio and growth opportunities through new data sources.
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Team Description The US Card Management Data Science team builds industry leading machine learning models to empower core underwriting decisions in the management of an existing credit card customer, such as credit limit increase.
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As a Quantitative Analyst 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 cloud 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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