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Geospatial Data Science Analyst
Tallahassee, FL, USA
This role uses data science to support geospatial data functions: data processing, modeling, analysis and visualization. This includes making simple modifications to existing processes, and providing support for more complex changes.
Support routine running of data processing, modeling, or analysis processes, as well as simple ad-hoc adjustments. May require updating of programming code in R, python, SQL, etc.; time series or regression modeling; creating maps; updating EXCEL and WORD documents; use of source control.
Perform exploratory data analysis as needed to support data processing, modeling, analysis or reporting. May require updating of box plots, histograms, LOESS models, kernel density estimation, maps.
Aggregate data or modeling results. Reports may be EXCEL or WORD documents, maps, interactive dashboards or web maps, or in other formats as needed. May require use of SQL, COGNOS business intelligence products, R, python, etc.
Data programming: Make simple/minor modifications to data processing, or provide support for complex modifications.
Modeling: Routine running and updating of statistical models, including data preparation; fitting or training models; and reporting results and diagnostics.
Analysis: Creation of simple aggregates and reports that support business decisions. Provide support for more complex reports.
Data processing may include use of SQL, SSIS, R, python, etc. Models may include time series, linear models, hierarchical models, credibility models, gradient boosted models, etc. Reports may involve significant writing and explanation, figures that will be presented to the public and legislative bodies.
Knowledge, Skills and Abilities:
Create mapping products, analytical models, and visualizations to support analytics and decision making.
Experience formulating, approaching, and solving problems on large datasets.
Intermediate knowledge of data programming
Scientific programming (R, C++, python, Fortran, etc.)
Solid data programming skills
Ability to create tables and figures
Ability to effectively work in a team environment
Troubleshoot data quality issues - identifying root cause/system & documentation/communication of resolution.
Utilize an array of data sources, all in different forms and with different tools or methods, to create a solution.
Required Education and Experience:
Bachelors Degree OR 4 years relevant experience, OR a combination of college education and relevant experience equivalent to 4 years.
At least 3 years of experience working with data retrieval, cleaning, or modeling; or quantitatively analyzing detailed data. Experience should have involved scientific programming language like R, C++, Python, etc. Master's (or educational equivalency w/in PhD program) Math, Statistics, Actuarial Science, ACAS, FCAS may substitute for 2 years of experience.
Education concentration in quantitative field, such as math, computer science, actuarial science, statistics, physics, etc., with some exposure to programming in classes, or through self-study, and math through vector calculus.
Posted 2018-09-12 under Analyst