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Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money.
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We are seeking a driven and analytically minded mid-level Data Scientist with a strong data science foundation and demonstrated expertise in machine learning and artificial intelligence.
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4+ years of experience working in data science, machine learning engineering, or data research, in a professional or academic environment. You’ll develop algorithms, write scripts, build predictive analytics, apply ML and deep learning, and use the right combination of tools and frameworks to turn that set of disparate data points into objective answers to help drive innovation, research, and development for our military and government leaders to make informed decisions.
$96,600 - $220,000 a yearFull-timeExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Experience in Beamforming, Adaptive Filtering, Antenna Modelling, Conformal Antennas, Iterative Solvers, and Machine Learning, Communications Signals, Modulation, Signal Intelligence (SIGINT), Software Defined Radios (SDR.
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As a Senior Reliability Engineer, you will play a critical role in ensuring the robustness, availability, and performance of our cutting-edge Data Engineering and Machine Learning Platforms.
$82,000 - $185,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Drive engagement and lead generation through targeted digital campaigns, email marketing, and search engine optimization (SEO) strategies. Neurodivergence, for example, attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, dyslexia, dyspraxia, other learning disabilities.
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Search Engine Optimization (SEO) Specialist. Conduct and present in-depth SEO audits of websites to identify technical SEO issues, on-page optimization opportunities, and areas for improvement in organic search performance and user experience.
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Experience with big data analytics, machine learning, artificial intelligence, or anomaly detection. 4+ years of experience with privileged and elevated access using cybersecurity tools, including Trellix Endpoint Security Suite (ESS), or McAfee HBSS, ePO, and FireEye tools, such as MVX, NX, HX, PX, IA, AX, IAS PCAP, or malware or forensics analysis solutions, and Palo Alto Firewalls, ForeScout, ACAS, or Splunk/Cribl.
$65,300 - $149,000 a yearFull-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
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We're seeking data scientists who have domain knowledge or an interest in Big Data, machine learning, natural language processing, image processing and an interest to apply it to economic and financial applications.
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As a Data Scientist at our client, you will play a crucial role in developing and implementing state-of-the-art machine learning models for use cases in traffic safety, mobility, and city planning.
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The Data Scientist will join a team responsible for developing advanced analytics products; applying Machine Learning, Artificial Intelligence and statistical programming tools to enterprise data to advance and enable key mission outcomes.
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CUDA (Compute Unified Device Architecture) /OpenCL (Open Computing Language) Programming: Develop and optimize applications using CUDA or OpenCL, harnessing the full potential of GPU hardware for parallel processing, high-performance computing, and machine learning on Linux platforms.
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The engineer will implement machine learning methodologies, identify trends within cyber data, work with data science models, integrate machine learning models into software, and collaborate with cross-functional team members.
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The Technology organization works to influence WMG's strategy and optimize day-to-day operations through data, insights, workflow, and machine learning, including generative AI. This position sits within the Technology organization, working closely with colleagues across WMG's recorded music and songwriting/publishing businesses.
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As part of a growing team this role will have the ability to leverage and work with new capabilities as they are deployed including deception infrastructure, continuous penetration testing, data loss prevention (DLP), and machine learning capabilities.
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