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5-7 years of experience in information security with a focus on hands-on security engineering, data protection, enterprise security, cloud security, and solutions architecture.
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Hands-on experience in programming with Java, Python or any development language. Hands-on experience with IaC tools such as Terraform, Ansible, ARM, CloudFormation.
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3+ years' professional experience programming with SQL, SAS, R, Python or other applicable programming languages (Mid Level/Senior) Participate with development and testing of Loan Servicing (Collections) processes to include new features, policies, and data in core servicing systems.
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Capital One is seeking a product owner to help deliver game-changing cybersecurity solutions based on threat, data, and design thinking. 2+ years of hands-on JIRA experience.
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Documentation/Procedures/Communications - Document all anomalies including discrepancies on and off air, general maintenance, video and/or audio loss, cue tones, closed captioning, equipment problems, and times of issues.
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Familiarity with Python or Matlab or Mathematica or C or a Quantum Language (Qisket). Typical summer projects may involve one or more of the following: numerical simulations; programming for data acquisition and data analysis applications; design and assembly of laboratory hardware, including mechanical, electronic, and cryogenic components; and participation in quantum measurements.
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As a federal contractor, Accura Engineering completed projects for the US Department of Defense including the Army Corps of Engineers, Army, Navy and Air Force for more than 10 years. Accura Engineering completed projects for the US Department of Defense including the Army Corps of Engineers, Army, Navy and Air Force for more than 10 years.
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Provide guidance and support to our data engineering team on Databricks-related issues. Hands-on experience to design and build solution powered by DBT models and integrate with Databricks.
$100,000 - $120,000 a yearFull-timeExpandApply NowActive JobUpdated 10 days ago - UpvoteDownvoteShare Job
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AI/ ML and RPA: Deep knowledge on AI/ ML solutions and/or RPA solutions and utilized them for solving a variety of outcomes like fraud detection, risk assessment, customer service automation, recommendations, trading, automating data entry, account reconciliation etc.
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Previous hands-on coding skills in languages commonly used in data engineering, such as Python, Java, or Scala. Hands-on experience in designing end-to-end architectures and pipelines that collect, process, and deliver data to its destination efficiently and reliably.
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Principal Data Architect - Telecom, Media & Technology - Senior Manager - Consulting - Location OPEN
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Demonstrated experience in leading large Data Engineering teams to design and build platforms with complex architectures and diverse features including various data flow patterns, relational and no-SQL databases, production-grade performance, and delivery to downstream use cases and applications.
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Minimum of 3 years of experience in a technical leadership role within a SaaS environment, with a proven track record in data engineering and analytics. The Professional Services Tech Lead is pivotal in delivering complex SaaS solutions, focusing on building innovative data and attribution models.
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Conduct data analysis using tools such as R, Python, Julia, SAS, SPSS, and/or Tableau. This branch focuses on leveraging big data, data visualization, artificial intelligence, and statistical methods to 1) identify and analyze health trends, 2) support health decision making, 3) enhancing disease surveillance, and 4) promote health equity.
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This team focuses on implementing all aspects of data analytics and data science, including data querying, visualization, predictive analytics, machine learning, artificial intelligence, and robotic process automation (RPA.
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Experience with Databricks for data engineering and exploratory data analysis. TheMachine Learning Engineerrole requires experience in Azure OpenAI, Large Language Models (LLMs), Python, and proficiency in developing applications using Streamlit, LangChain, Databricks, and Python frameworks like Flask and FastAPI. The ideal candidate will be adept at building scalable machine learning models and deploying them to production environments, and also being part of customer success teams.
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