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Certifications in relevant areas such as data science, machine learning, or project management (e.g., Google Cloud). Experience with natural language processing (NLP), computer vision, or other specialized areas of machine learning.
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Familiarity with cloud platforms that offer specific support for deploying and scaling generative models, such as Google's Vertex AI, Azure's AI tools, and AWS's Machine Learning services.
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5+ years of experience in data analysis or data science, with 3+ years focusing on machine learning problems, ideally in a relevant space (KYC, sanctions detection, anti-fraud detection, treasury management, crypto/blockchain data science.
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Demonstrated interest in AI technologies and willingness to learn how AI can enhance HRIS platforms like Workday, including basic understanding of machine learning concepts, natural language processing, and predictive analytics.
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We're doing this by leveraging the power of patterns (Anti-Corruption Layering, Strangler fig, Microservices, Event Sourcing, etc) and technologies (Kafka, Solace, Change Data Capture, Node.js, Go, Containerization, PaaS) to build cloud-native solutions for the enterprise based on modern event driven architectures.
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Experience working with cloud based data warehouses like Google BigQuery, Redshift, or Snowflake. Bachelor’s or Graduate degree, Field of Studies required: In a quantitative field or commesurat experience such at Statistics, Business Analytics, Data Science, Applied Math, Econometrics or Operations Research.
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Strong understanding of cloud security (AWS, Azure, Google Cloud). EDB provides a data and AI platform that enables organizations to harness the full power of Postgres for transactional, analytical, and AI workloads across any cloud, anywhere.
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Experience responding to cyber events in public cloud environments such as AWS, Azure, Google Cloud, etc. The Cyber Incident Response Analyst is responsible for responding to both existing and emerging threats, as well as identifying attacker tools, tactics, and procedures by analyzing data from a variety of sources and tools.
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In supporting rule analysis, Teammate should be able to Independently perform sophisticated data analytics that fit to the fraud problem being observed (ranging from classical econometrics to machine learning, neural networks, and natural language processing) in a variety of environments using structured and unstructured data.
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Extensive experience in cloud migration projects, with proficiency in cloud platforms such as Azure, AWS, or Google Cloud. Technical Expertise and Guidance: Utilize deep technical knowledge in cloud technologies, data management, and healthcare systems to guide project decisions and overcome technical challenges.
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Certifications such as AWS Certified Solutions Architect, Azure Solutions Architect Expert, or Google Professional Cloud Architect are a plus. Proficiency in cloud platforms such as AWS, Azure, and Google Cloud Platform, with hands-on experience deploying and managing cloud resources.
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Application spaces of algorithm development include graph theory optimization and quantum machine learning. Familiarity with Python or Matlab or Mathematica or C or a Quantum Language (Qisket.
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You will assist clients in choosing a platform, defining their data needs and migrating them to a modern cloud data environment using cloud providers such as Azure, Google Cloud Platform, Amazon Web Services, Snowflake, Databricks or Teradata.
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Key word search: Python, Master's degree, predictive maintenance, preventative maintenance, relocation package, data science. Develop internal APM product utilizing the latest anomaly detection machine-learning algorithms for predicting machine failures.
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Metas Solutions has an "immediate" opening for an experienced Data Scientist/Machine Learning Engineer to work Remotely. The Data Scientist/Machine Learning Engineer will have strong analytical skills and experience in using Posit and RStudio to join our team.
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