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Collaborate with cross-functional colleagues (e.g., clinical scientist, study statistician, programmer) to develop data visualization application, statistical modeling and algorithm in R to address issues in clinical data quality.
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Provide statistical and mathematical support to analyze and interpret a wide range of data to help the agency understand the value of GEOINT to the community and support strategic resource decisions made by the agency leadership.
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Ability to apply expertise of research methodology, psychometrics, and statistical analysis of complex behavior using varied data sources and formats. 10+ years of experience as an operational psychologist, national security psychologist, forensic psychologist, personnel psychologist, police psychologist, military psychologist, or corrections psychologist.
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Collect and analyze data using statistical and Artificial Intelligence /machine learning algorithmsSupervise and assist undergraduate students working on research projects and act as a liaison/mediator between undergraduate students and the faculty researcher.
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Ability to develop persistent applications for statistical or machine learning processes using SQL, R, Python, SAS, or SPSS. Certification in business analytics, data mining, or statistical analysis.
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Basic knowledge and experience in statistical and data mining techniques such as: generalized linear model (GLM)/regression, random forest, boosting, trees, text mining, hierarchical clustering, deep learning, convolutional neural network (CNN), recurrent neural network (RNN), T-distributed Stochastic Neighbor Embedding (t-SNE), graph analysis, etc.
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Experience in building statistical models using R, Python, STATA, or a related software. Strong publication and presentation record in top-tier economic, public policy, statistical, or ML publications and conferences.
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We look for our Summer Associates to use and further develop their economic research abilities as well as their analytical and statistical skills on cases spanning a wide range of subjects, including antitrust, accounting, competition policy, class actions, intellectual property, labor and employment, among others.
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The role will apply statistical programming, modeling, visualization techniques, data mining, and forecasting skills to analyze challenging public sector problems. At least four years of experience developing scalable, production-ready NLP solutions using sci-kit learn, Keras, TensorFlow, PyTorch, Spark NLP.
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Proficiency in data analysis and statistical techniques, including experience with software such as R, Python, or MATLAB , to effectively analyze experimental results and draw meaningful conclusions.
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The GPS AI & Data Engineering offering is responsible for developing advanced analytics products and applying data visualization and statistical programming tools to enterprise data in order to advance and enable the key mission outcomes for our clients.
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Data Management Analysts (Data Management, Data Governance, Data Quality, Test Data Management, Data Architecture, Data Security, Programing (SQL, JAVA, Python, R), Data Analysis Software (e.g., Excel, SAS, SPSS), Knowledge of Database Query Language (e.g., SQL), Report Creation and Data Visualization (Tableau and R Studio) , Understanding of Statistical Methods and Techniques to Analyze Data.
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Responsibilities Working with the Director of Employer Relations, the incumbent serves as a coordinator for the on-line career services software, SIPA Connect, maintaining the software system, designing announcement pages, instructing students on the software's use, troubleshooting problems, and providing statistical research reports generated by the software program.
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Advanced proficiency with commercial off the shelf (COTS) statistical software or tools for data visualization (i.e., SPSS, SAS, MatLab, Tableau, etc. Knowledge of process improvement methodologies such as Robotic Process Automation, Lean Six Sigma, Kaizen, Total Quality Management, or similar.
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Machine learning/AI including but not limited to regression techniques, neural networks, decision trees, clustering, pattern recognition, probability theory, stochastic systems, Bayesian inference, statistical techniques, deep learning, supervised learning, and unsupervised learning.
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