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Using tools such as Palantir Foundry, they will also work with cutting-edge DevOps technologies, develop advanced analytics products, and apply data pipelining and statistical programming tools to enterprise data to advance and enable key mission outcomes.
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Some of the cutting-edge technologies we have recently implemented are Kafka, Spark Streaming, Presto, Airflow, and Kubernetes. Passion for engineering and computer science around data.
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Apply a variety of spatial data science techniques to tackle customer challenges to include geospatial statistics, spatial optimization, spatial pattern analysis, geospatial artificial intelligence, spatial autocorrelation, activity-based intelligence, imagery analysis, remote sensing, and geospatial data visualization approaches.
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As a big data engineer at Booz Allen, you'll implement data engineering activities on some of the most mission-driven projects in the industry. We need an experienced data engineer like you to help our clients find answers in their big data to impact important missions—from fraud detection to cancer research to national intelligence.
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Certification Preference : AWS Certified Solutions Architect, Google Certified Cloud Professional Cloud Architect, Azure Solutions Architect Expert. Relevant certifications include AWS Certified Solutions Architect, Google Professional Cloud Architect, Azure Solutions Architect Expert.
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As a Capital One Sr. Director of Software Engineering, you'll work on everything from customer-facing web and mobile applications using cutting-edge open source frameworks, to highly-available RESTful microservices, to back-end Java based systems using the hottest techniques in Big Data. You'll bring solid experience in emerging and traditional technologies such as: node.
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Familiarity with cloud-based computing solutions (AWS, Google Cloud) for scalable data analysis. Utilize cutting-edge algorithms and computational techniques to uncover insights from multi-omics data, offering solutions tailored to specific client needs.
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At least 2 years of experience with Cloud Native technologies (Amazon Web Services, Microsoft Azure, Google Cloud Platform) Collaborate with digital product managers, and deliver robust cloud-based solutions that drive powerful experiences to help millions of Americans achieve financial empowerment.
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CT State CC-Campuses Courses include the following: Astronomy Biochemistry Biology Cannabis Studies Chemistry Data Science Earth Science Environmental Science Geography Horticulture Mathematics Natural Resources Physics These positions are on continuous recruitment, and are filled on an as-needed basis, depending on course offerings, enrollment and specific department needs.
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This role is perfect for someone who thrives at the intersection of data science, data engineering, and business intelligence, and enjoys working closely with Federal clients to drive strategic decision-making through data-driven insights.
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Bachelor’s or Master’s in computer science, Data Science, or related fields, with a strong focus on NLP/LLM and cloud solutions. We are actively seeking a specialized Healthcare AI DevOps Engineer (NLP / LLM) well-versed in AWS and experienced with cutting-edge open-source Large Language Models (LLMs) like Llama and Qwen, and familiar with using frameworks like Hugging Face for model implementation.
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We integrate off-the-shelf and new development efforts to sustain and enhance Defense Intelligence Agency's (DIA) National Media and Exploitation Center (NMEC) architecture by leveraging cloud-based computing, artificial intelligence (AI), machine learning (ML), and cross-domain transfer systems to provide cutting-edge data exploitation, enrichment, triage, and analytics capabilities to Defense and Intelligence Community members.
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Our experts in public health, performance evaluation, and health operations solve the complex problems faced by civilian and military customers alike by leveraging advanced tools including digital transformation, artificial intelligence, data analytics, cloud enablement, modeling, and simulation, and more.
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At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud) 3+ years of experience with AWS, Google Cloud Platform, Microsoft Azure, or another cloud service.
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One active Google Cloud Certification including Google Cloud Professional Cloud Architect or Google Cloud Professional DevOps Engineer is preferred. A skilled and passionate DevOps engineer with a solid foundation in Google Cloud Platform and a desire to work in a dynamic, collaborative environment.
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