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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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Requirements: Requires a Master’s in Statistics, Computer Science, Data Science, Machine Learning, Applied Math, Operations Research, Economics, or a related field plus two (2) years of experience as a Data Scientist, Data Engineer, or other occupation/position/job title involving research and data analysis.
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Experience with common data science tools such as Python, R, PyTorch, TensorFlow, Keras, NLTK, Spacy, or Neo4j, and a good understanding of modeling platforms such as Azure AutoML, SageMaker, DataBricks, DataRobot, and H2O.ai.
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Programming:Languages: Familiarity or proficiency in languages commonly used in data science, like Python, R, or Scala. Transform your career to the next level with GDIT as a Solutions Architect where you can elevate your skills in Data Science, Machine Learning, or leading AI techniques and technology expertise into solutions in support of our Government customers.
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Good knowledge and Proven practical experience in migrating relational data base from on-prem to cloud OR to build cloud-based data lake using either Big Data / Azure Synapse / Databricks / Snowflake.
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We are hiring a Senior Statistical Analyst to leverage cutting-edge data science tools and methodologies on real-world clinical data for scientific research in precision medicine.
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A Master's or PhD degree in biostatistics, data science, biomedical informatics, epidemiology, public health, computer science, applied mathematics, engineering, or a related field.
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Exposure to cloud platforms and big data systems such as Hadoop HDFS, Hive is a plus. 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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Requires proficiency in SAS, R, or Python (preferred) for data wrangling, automation, and creating statistical and machine learning models. Desire proficiency in cloud-based computing and data platforms (Azure, Google Cloud, BigQuery, Snowflake, DataBricks.
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The Associate Director of California River Restoration and Data Science will help American Rivers compile and analyze watershed and species data to evaluate the most pressing climate challenges our rivers face.
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A minimum of three (3) years of experience using R programming language (Python is a plus) Join a rapidly growing team of professionals working to build a world-class data science practice with a focus on solving real-world health challenge and reduce the health disparities.
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Knowledge of machine learning and AI methods and proficiency with scripting and executing data analytics algorithms and models with hands-on experience using a modeling and simulation software (e.g. Python, MATLAB, R, NONMEM, SAS, S-Plus, etc) is a must.
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Self-driven, challenge-loving, detail oriented, teamwork spirit, excellent communication skills, ability to multitask and manage expectationsNice to have:Experience in any of: machine learning, analytics, data mining, or data mart and warehouseExperience with Deep Learning platforms (Tensorflow/Keras/Spark MLlib) and SQL/Unix/ShellExperience with machine learning algorithms, NLP, and/or statistical methods a big plusYahoo is proud to be an equal opportunity workplace.
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Expertise in common data science toolkits and programming languages, including R, Python (including SciPy, NumPy, and/or PySpark) and/or Scala, Java, SQL, and shell scripting. Medical Device endpoint protection Qualifications for success: Bachelor’s Degree in Data Science, Computer Science, Information Systems, Mathematics, Statistics, Engineering or similar (Masters Preferred) Experience with a range of machine learning techniques: linear regression, classifications, random forest, clustering, supervised and unsupervised learning, graph algorithms, etc.
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You will also identify and analyze the real-world clinical data to address scientific questions, define data strategy, build statistical analysis methodology and plan, and help us building solutions and tools to help answer complex clinical research questions, with a focus on health disparities.
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big data science a plus r jobs Company: Endeavor
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