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Minitab, SAS, Matlab, VBA – knowledge of optimization engines such as CPLEX or Gurobi is a plus)Proficiency in any data visualization software (e.g., Power BI, Tableau, Qlik, D3, Shiny)Theoretical or practical experience in mathematical optimization techniques ( e.g. linear and non-linear optimization, mixed integer programming, sensitivity analysis, constraint programming etc.
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Handle highly confidential information with discretion and manage, support, and prepare documentation, records, and data input within the student information system (Banner), the clinical tracking system (Tevera), and the ATI learning system.
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We are working on challenging projects, migrating ETL jobs from Talend to DataBricks, building workflow automation solutions using Microsoft Power Platform, data flows with Azure data lake storage and DevOps environment set up.
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As a Senior Instrumentation & Controls Engineer with Middough, you will collect and prepare data/information and perform detailed engineering calculations. We offer a growth and learning culture which encourages and supports employee development through a wide variety of tools and resources such as the company Learning Management System, Middough Learning Center.
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5+ years experience in AWS (or other clouds) relevant to machine learning including data processing & storage, API development, MLOps, CI/CD pipelines, and container orchestration (preferably ECS & EKS.
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Innovation: Focus on the development and application of new methodologies, technologies, and techniques to gather data and insights including Machine learning AI, Mobile Optimized Surveys, Gamification, Behavioral economics, real-time feedback, Multimodal surveys, Blockchain technology, Virtual and Augmented reality.
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Strong knowledge of PySpark, Airflow, and data pipelines; strong knowledge of Sagemaker and machine learning pipelines. Automate and streamline the end-to-end machine learning workflow, including data ingestion, feature engineering, model training, evaluation, and deployment.
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With applications in machine learning Data management skills (e.g. data modeling, data integrity QA/QC, querying, analysis) Data science programming/coding in Python and/or R including use of spatial libraries/packages (eg GeoPandas, Rasterio, GDAL/OGR, Terra) Business Intelligence/data visualization platforms such as Tableau, Power BI, etc.
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Data-driven, evidence-based learning and instructional models, including SESI’s own positive behavioral interventions and support (PBIS) framework called CASE.An attractive and robust suite of benefits, including comprehensive healthcare benefits, 401(k) with employer match, employee assistance program, mental health support, fertility and family building, and more.
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Proficiency with advanced data science techniques, such as neural networks, natural language processing (NLP), or unsupervised learning methods. Define scalable data model requirements and collaborate closely with Data Engineering for successful implementation and maintenance.
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Applying the latest techniques and approaches across the domains of data science, machine learning, and AI isnt just a nice to have, its a must. In this role you will design and implement algorithmic product architectures to bring our machine learning models to life across the full lifecycle of the product including data ingestion, ML processing, and results delivery/activation.
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Working closely with the Director, Operations and Volunteers, engage in recruitment, training, and ongoing management of a core of 100 volunteers that support the Ryan Learning Center: maintain volunteer schedules and data; provide clear and timely communications to volunteers; collaborate on the development of the annual training calendar and lead trainings as appropriate; provide oversight to volunteers on duty; engage in performance management as necessary.
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This role will be part of a multidisciplinary actuarial/data science team designing and delivering powerful, analytical tools utilizing statistical modeling, machine learning, and advanced data engineering techniques to enhance and overhaul core actuarial processes.
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2+ years of industry experience in a computational area such as data science, computer science, machine learning, artificial intelligence, statistics, or graph algorithms. In this role, you will lead and contribute to new and ongoing research and development efforts that advance Epsilon's identity match abilities - leveraging data science, machine learning and other disciplines to create new data-driven capabilities for our real-time digital marketing business.
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Deep HR process, data architecture, reporting and security knowledge in Workday Core HCM, and at least 1-2 other process areas/SKUs – Talent Acquisition, Talent Management, Career Hub, Compensation, Learning and Journeys.
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data learning jobs in Addison, IL
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