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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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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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Apply fundamental and advanced quantitative methods, including machine learning and statistical modeling, to solve complex business problems and enable data-driven decision-making (e.g., build statistical and machine learning models for trend analysis and forecasting to predict future business outcomes for a Fortune 100 company.
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Advanced knowledge of cloud computing technologies such as Apache Spark, Azure Data Factory, Azure DevOps, Azure Client (Machine Learning), Hadoop, Microsoft Azure, Databricks, AWS, Google Cloud.
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Utilize and develop queries and reports from the HRIS system (PeopleSoft), CAVE, and Cognos using appropriate data science and business intelligence tools (Python, R, SQL, Tableau, Microsoft Office,); and analyze data using descriptive (e.g., means, percentages) and inferential statistics (e.g., ANOVA, t-test, regression modeling techniques.
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Utilizing NVDA (NVIDIA) technologies such as CUDA, TensorRT, and GPU acceleration to optimize machine learning models and enhance the overall performance of applications. Additionally, expertise in NVDA (NVIDIA) technologies such as CUDA, TensorRT, and GPU acceleration will be crucial in optimizing our machine learning models and enhancing the overall performance of our applications.
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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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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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We want Data Science, Machine Learning, Data Analyst, and Java Full Stack candidates. Knowledge of Statistics, Gen AI, LLM, Python, Computer Vision, data visualization tools.
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Develop data science applications for visual inspection and classification, anomaly detection, predictive maintenance, NLP, or root cause analysis using computer vision, machine learning and deep learning.
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Experience with developing / overseeing development of analytical dashboards using a variety of tools/packages, e.g. Tableau, Python, R, Alteryx, Powerapps, UI Path etc. Master’s degree in data science, business, sciences statistics, data mining, applied mathematics, business analytics, engineering, computer science or related field (MBA Preferred.
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IEMS offers an undergraduate degree and a machine learning & data science minor, a PhD program, and master's degrees in machine learning & data science and in engineering management.
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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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Apply machine learning, econometrics/statistics, predictive modeling, return-on-investment analysis, simulation, and data visualization methods to support the development of health policy.
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Preferred Qualifications: Prior experience in ad platform, auction systems, or dual-sided marketplace 2+ years of experience as a developer, data scientist or machine learning engineer Hands-on experience with cloud technologies and service oriented architectures Track record of using data analytics for improving SW operations and organizational efficiency Advanced degree in an analytical field.
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machine learning open source data engineering r python jobs Company: Diverse Lynx
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