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Must have knowledge of advance data science methods; examples include prescriptive, cognitive algorithms, big data analytics, commercial and open source Hadoop, data-mining, Python, “R”, machine learning, or NLP.
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Possession of relevant certifications such as CISSP (Certified Information Systems Security Professional), CISM (Certified Information Security Manager), CCNA (Cisco Certified Network Associate), Security+, or PCNSE (Palo Alto Certified Network Security Engineer) is desirable, but not required.
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Leading the consolidation and implementation of new concepts and processes in areas including information retrieval, distributed computing, large-scale system design, networking, data storage, security, artificial intelligence, natural language processing, UI design, and mobile.
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Optimize the performance of data pipelines, ETL processes, and machine learning workflows on Databricks. Implement and enforce security best practices, including encryption, network security, and data access controls.
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You will report directly to the Learning and Development Manager and work closely with subject matter experts, trainers, and other stakeholders to create engaging, effective, and innovative learning materials.
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Two (2) years of experience with applying statistics and psychometrics concepts, including classical test theory, item response theory, structural equation modeling, and mixed-effects modeling; applying AI and machine learning to measurement in education; educational data mining; scientific programming environments (R, Python, Stata, and/or MATLAB scripting); and/or, mathematical foundations of modern statistical and machine learning methods.
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Handling patent prosecution matters related to data science, AI, networking technologies (especially network security), machine learning/artificial intelligence, and hardware security.
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Development & Support: Lead Data Engineer, Senior Machine Learning Engineer, Big Data Engineer, Senior Data Engineer, Principal AI Engineer, AI/ML DevOps Engineer.
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Demonstrable experience building data pipelines, transformations, analytical environments Demonstrable experience with Azure Data Platform (Synapse, SQL, Cosmos DB, Databricks, Machine Learning workspace) Collaborate with Product Managers, Solution Architects, DevOps and Information Security teams to understand data requirements for software development in an Agile environment Compose and maintain detailed design specifications and component documents.
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Examples include Azure Machine Learning Studio, Google’s Vertex AI, IBM Watson Studio, Amazon SageMaker and open-source tools like Kubeflow. Examples include MPP data warehouses like Snowflake and Amazon Redshift and all-in-one Apache Spark platforms like Databricks.
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Senior / Principal Recruitment Consultant - AI, Machine Learning & Data Germany / DACH. Areas: Data, Artificial Intelligence, NLP, Computer Vision, Recommender Systems, LLM's, Quantum Computing, Machine Learning, Deep Learning, Bioinformatics.
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The role requires proficiency in patent prosecution, with a preference for expertise in electrical engineering, software-related technologies, data science/AI, networking technologies (especially network security), machine learning/artificial intelligence, and hardware security.
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Python ecosystem preferred, R will be acceptable, machine learning libraries & frameworks (e.g. TensorFlow, PyTorch, scikit-learn) and familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI.
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Advanced knowledge of Apache Spark, Azure Data Factory, Azure DevOps, Azure Machine Learning, Hadoop, Hive (Apache), Informatica, Microsoft Azure, Databricks, Microsoft Power BI, Microsoft SharePoint, Microsoft SQL Server, MS Office Products or Operational Data Integration (OLTP.
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Preferred expertise includes patent prosecution in electrical engineering or software-related technologies, data science/AI, networking technologies (especially network security), machine learning/artificial intelligence, and hardware security.
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