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The statistical programmer works collaboratively with the end users, internal colleagues to ensure the high-quality production of data visualizations and statistical outputs using Spotfire/R and other visualization tools.
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Overseeing teams and programs analyzing and defining data requirements and specifications using various tools and methodologies (e.g., Statistical Package for Social Sciences [SPSS], Statistical Analysis System [SAS], R Analytics, Statistics and Data [STATA]) to discover new patterns and behaviors providing DHS Headquarters (HQ) and/or Component stakeholders actionable recommendations.
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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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Statistical Background: Proficiency in statistics and machine learning techniques, particularly when applied to meteorological data. Data Visualization: Effective data visualization skills for time series and geospatial data.
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Expertise in R or Python Knowledge in multiple of the following programming languages: R, Python, Stata, SAS, SQL Experience in at least one of the following areas: natural language processing, GIS, and data visualization (especially interactive data visualization) SALARY AND BENEFITS: The pay range for this position is $88,000 – $157,000.
$88,000 - $157,000 a day (equity)ExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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Using Jupyter notebooks and one or more statistical visualization or graphing toolkits such as Excel, Qlik Sense or Tableau. Min 4 years of experience as a Data Scientist in the ad-tech industry, including the following experience in: business intelligence, data mining, analytics, and statistical modeling disciplines.
ExpandApply NowActive JobUpdated 9 days ago - UpvoteDownvoteShare Job
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Understanding of data models, large datasets, business/technical requirements, BI tools, statistical programming languages and librariesDemonstrates functional knowledge of data visualization libraries such as matplotlib or ggplot2; knowledge of other visualization tools such as Microsoft Power BI , Quick Sight or Tableau.
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Your expertise in data visualization, statistical analysis, and proficiency in web development technologies will contribute to the success of our data-driven initiatives. Experience with front-end frameworks/libraries such as React, Angular, or Vue.js to enhance interactive data visualizations.
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Proficiency in statistical analysis, data mining, predictive modeling, and data visualization tools (e.g., R, Python, SQL, Tableau, Power BI). Technology and Tools: Evaluate and implement advanced HR analytics tools, technologies, and platforms to enhance data visualization, reporting capabilities, and self-service analytics for HR stakeholders.
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Using tools such as Snowflake and/or Databricks, they will also work with cutting-edge DevOps technologies, develop advanced analytics products, and apply data and statistical programming tools to enterprise data to advance and enable key mission outcomes within cloud environments (GCP, AWS, Azure.
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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 with analytical / statistical programming tools for data extraction and summarization, statistics, visualization and analysis (Alteryx, SAS, SQL, R, Tableau, etc. Deeper experience than Consulting Research Analyst Associate in analytical / statistical programming tools and in the ability to extract, summarize, and visualize data for requests.
ExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Basic understanding and working with data management software, geographic information systems (GIS), statistical programs (R) (SAS) (STATA) (SPSS), and relational database systems (SQL, Oracle Business Intelligence.
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Proficient in data modeling, statistical analysis, and predictive modeling techniques, alongside a strong understanding of data visualization best practices and design principles.
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Proficient with Python, SQL, Graph/Vector databases/theory, R and visualization tools. MS or PhD in Computer Science, Statistics, Applied Mathematics, Physics or other quantitative fields with focus on AI, Machine Learning, Mathematical Algorithms, Probability and Statistical Modeling.
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