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A Bachelor's degree in Math, Applied Mathematics, Math Education/Math Teaching, Education with a Concentration in Mathematics, Computer Science, Statistics, Physics, or Engineering, OR a Bachelor's degree with at least 18 undergraduate credit hours of math courses (Calculus II and above)A current State of Colorado Professional Teacher License with Mathematics Education 7-12 Endorsement.
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Hands-on experience of machine learning methodologies including advanced analytics tools (such as R and Python) along with applied mathematics, ML and Deep Learning frameworks and libraries (TensorFlow, PyTorch, Keras) and ML techniques.
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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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Solid foundation in finite element analysis, solid mechanics, and applied mathematics. Required Qualifications: PhD in Mechanical Engineering, Electrical Engineering, Ocean Engineering, Applied Mathematics, or Applied Physics (minimum.
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Relevant degree in geospatial related field such as: Geography, Geology, Environmental Science, Remote Sensing, Urban Planning, Statistics/GeoStatistics, Applied Mathematics, or Computer Science.
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Education : A higher education degree (MSc or PhD level) in fields such as economics, engineering, mathematics, computer science, statistics, applied physics, meteorology, or equivalent.
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A master s degree or PhD in Computer Science, Statistics, Applied Mathematics, or a related field, with at least 5 7 years experience in data science or a similar role. 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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Experience with cloud computing environments (AWS, Azure, or GCP) and Data/ML platforms (Databricks, Spark). Experience in Supervised and Unsupervised Machine Learning including classification, forecasting, anomaly detection, pattern recognition using variety of techniques such as decision trees, regressions, ensemble methods and boosting algorithms.
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Relevant certifications such as Microsoft Certified: Azure Data Scientist Associate or AWS Certified Machine Learning are advantageous. The incumbent will lead and help to develop a newly formed data-scientist team in delivering impactful analytical solutions, ensuring these innovations are seamlessly embedded into business operations to drive decision-making, enhance operational efficiency, and foster a culture of continuous improvement and innovation.
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We're look for a Lead Data Scientist to spearhead the design, development, implementation and maintenance and improvement of advanced data science initiatives across business units, directly aligning with strategic objectives.
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Expertise in advanced analytical techniques (e.g., descriptive statistics, machine learning, optimization, pattern recognition, cluster analysis, etc.) Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, monitoring, and feedback loop.
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Foster a culture of innovation and continuous improvement and lead the exploration and adoption of new data science technologies and methodologies to contribute to the advancement of analytics' expertise.
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Provide input to the long/term plan for the Data Science team, including key focus areas, talent acquisition, input to technology platforms, and interaction model with the rest of the organization. Proficient in at least one analytical programming language relevant for data science.
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This role encompasses transforming innovative ideas into real-world solutions through the application of sophisticated analytical techniques such as machine learning, optimization, and cluster analysis.
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Proven track record of recruiting, training, and retaining a skilled data science team, identifying talent gaps, and addressing them. Demonstrated ability to lead and manage data science projects, including, managing workflow and priorities, to ensure timely delivery of projects with high-quality outcomes.
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applied mathematics jobs Title: product manager strategy
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