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Utilizing Data analytics skills and experience developing mathematical models in R, Python, SAS, MATLAB, and/or SPSS; Preparing and modeling data in SQL, Tableau, and/or Qlik.
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Display analytic results in text and visually using appropriate data science, business intelligence, and visualization tools, such as Python, R, SQL, Tableau, PowerPoint, Excel, and communicate results to client audiences at all levels with presentations and briefings.
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Skilled in data visualization and use of graphical applications, including Microsoft Office (Power BI) and Tableau; major data science languages, such as R and Python; managing and merging of disparate data sources, preferably through R, Python, or SQL; statistical analysis; and data mining algorithms.
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Experience in data access tools, such as SAS, SQL, Python, and R. Knowledge of CMS claims data, including Medicare, Medicaid, and Marketplace, in the IDR or CCW environment with Fee-for-Service (FFS), Medicare Advantage encounter data, Medicaid data in the Transformed Medicaid Statistical Information System (T-MSIS), or Prescription Drug Event (PDE) data.
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Technology Tools: AWS, Open Search and Python Data Science tools. Technologies to know: Statistical Tools may include: SAS, R, SPSS, Matlab, Mahout/MADlib, Stata. Conferences (recently attended by Praxis employees): AWS Summit, IoT World, Black Hat and DefCon. Training & Certifications: Splunk, AWS, Big Data/Cloudera, VMWare, Scrum Master.
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8+ years of experience using SAS, R, Python, or SQL in a research, consulting, or business environment. 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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Basic coding knowledge and experience in several languages for example: R, Python/ Jupyter, SAS, Java, Scala, C. Basic to substantial experience in one or more of the following commercial/open-source data discovery/analysis platforms: RStudio, Spark, KNIME, RapidMiner, Alteryx, Dataiku, H2O, SAS Enterprise Miner (SAS EM) and/or SAS Visual Data Mining and Machine Learning, Microsoft AzureML, IBM Watson Studio or SPSS Modeler, Amazon SageMaker, Google Cloud ML, SAP Predictive Analytics.
$184,000 - $248,400 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Exploratory data analysis, model building, and regression analysis using languages such as Stata, R, Python, or SAS.Qualifications:. , SAS, Stata, MS SQL Server, R, MS Access, SPSS.
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Experience with statistical software (e.g., R, Python, MATLAB) and database languages (e.g., SQL). Deliver business-critical projects within the health technology portfolio including health and fitness data quality and analysis, offline health data collection, emergent health data technologies analysis and discovery, survey design and management, health research support, and Program health data initiatives.
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Proficiency with input-output or general equilibrium economic modelling tools such as Esmi, IMPLAN or REMI.Proficiency with Stata, R, Python and other programming languages. Functional experience in at least one of the following areas desired, but not required:Proficiency with urban data science analytical techniques and familiarity using multiple public datasets including BLS, BEA, NAICS data, ACS and other geographically-defined socioeconomic datasets.
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3+ years in a hands-on role performing advanced predictive analytics using tools like Python, R, or Scala. Proficient understanding of relational (e.g. Oracle, SQL Server, PostgreSQL) and Big Data distributed structures (Hadoop/Spark) in order to source data effectively.
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Will provide support on a number of payment model implementation contracts requiring intermediate SAS, R, Python, or SQL experience as well as knowledge of statistics and research methodology.
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Pre-processing - Demonstrate the skills and experience to collect, clean, and prepare data sets for input into a computational model using technologies such as Python, SAS, or R. Strong candidates will explain various methods you have applied using common pre-processing functions such as stop word removal, stemming, lemmatization, and tokenization.
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Analytics Expertise: Serve as a subject matter expert across our solutions offerings such as database marketing, marketing campaign reporting, investigative descriptive analytics, and propensity modeling while leading and individually contributing to analysis tasks including Excel, R, SQL, Python, and SAS.
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Data analysis, modeling, and visualization using R, Python, or similar software. This position will primarily support the Physical Metallurgy branch at the Naval Surface Warfare Center, Carderock Division and concentrate on investigations of Naval structural alloy systems, such as high-strength steel, aluminum, nickel aluminum bronze, and/or titanium alloys.
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