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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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Lead and participate in solutioning sessions, working hand-in-hand with businesses/clients, translating business objectives into actionable machine learning/data science use casesWhat You'll Bring.
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Expertise in a subset of the following: machine learning, object detection, image segmentation, computer vision, image processing, remote sensing, spectral science, neural models for autonomous vehicles/robotics, structure from motion (SfM), natural language processing (NLP), large language models, data fusion, change detection, and pattern of life analysis.
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Cellular 4G/5G Firmware Data Science & Machine Learning Engineer Do you have a passion for invention and self-challenge? Data Science & Machine Learning Engineer will be responsible for developing state-of-the-art data processing pipeline based on machine learning models and leveraging data science algorithms to parse substantial data and logs in a timely manner to automatically tackle the issues or provide recommendations for the next step of solving problems.
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The search is for candidates in optimization with applications in machine learning & data science, computational social science, healthcare, or logistics & operations.
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Background in python and the data science stack (numpy, scikit-learn, etc), and deep learning frameworks such as PyTorch, TensorFlow, etc. Oversees others in extracting data from existing databases or literature and preparing data for statistical machine learning analysis.
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Experience leveraging complex data to drive business decisions, hands on experience in data science methodologies (predictive analytics, machine learning, patient level data triggers) using R, Pytong, Databricks and deep knowledge of Qlik, PowerBI, Tableau for visualization.
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The University of Southern California's Leonard D. Schaeffer Center for Health Policy and Economics is now accepting applications for one or more Postdoctoral Fellowships in health policy, health economics, and health services research with a specific focus on machine learning and data science applications in health economics and outcomes research (HEOR) and pharmacovigilance.
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More specifically the Senior Full Stack Developer we are seeking is a highly skilled Sr. Full Stack Developer who is tasked with implementing state-of-the-art Retrieval-Augmented Generation (RAG) architecture and utilizing NVDA and open-source technologies.
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Required Skills for Data Science/Data Analyst/AI/Machine Learning Positions Associate, Bachelor's, or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, Information Systems, IT, Statistics, Mathematics, or having good logical aptitude.
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Qualifications We DesireMaster’s degree in Computational Biology, Computational Bioengineering, Machine Learning, Statistics, Computer Science, Mathematics, or a related field. Qualifications Bachelor’s degree in Machine Learning, Computational Biology, Statistics, Computer Science, Mathematics or a related field, or the equivalent combination of education and related experience.
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Expert-level knowledge of data frameworks, data lakes and open-source projects such as Apache Spark, MLflow, and Delta Lake. Bachelor‘s or Master‘s degree in Big Data, Computer Science, Engineering, Mathematics, or similar area of study or equivalent work experience.
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2+ years of experience as a developer, data scientist or machine learning engineer. 11+ years of experience spanning Engineering / Data Science / Technical Program Management leading cross-functional efforts in the software or tech industry in a data-driven environment.
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Experience with data visualization tools (e.g. Grafana, Looker, Tableau, DataStudio) building dashboards, source control (e.g. GitHub), ticket management (e.g. JIRA) Some of the key areas that the Technical Program Manager will drive will include Infrastructure cost, service availability, observability of data pipelines and capacity planning.
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Oversee the implementation of data processing workflows, analytics, and machine learning models using Databricks. This role requires a deep understanding of big data technologies, particularly Apache Spark, as well as expertise in data engineering and analytics.
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machine learning open source big data science jobs Title: software developer
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