Student Veterans of America Jobs

Welcome to SVA’s jobs portal, your one-stop shop for finding the most up to date source of employment opportunities. We have partnered with the National Labor Exchange to provide you this information. You may be looking for part-time employment to supplement your income while you are in school. You might be looking for an internship to add experience to your resume. And you may be completing your training ready to start a new career. This site has all of those types of jobs.

Here are a few things you should know:
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  • Jobs on this site are original and unduplicated and come from three sources: the Federal government, state workforce agency job banks, and corporate career websites. All jobs are vetted to ensure there are no scams, training schemes, or phishing.
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  • The newest jobs are listed first, so use the search features to match your interests. You can look for jobs in a specific geographical location, by title or keyword, or you can use the military crosswalk. You may want to do something different from your military career, but you undoubtedly have skills from that occupation that match to a civilian job.
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Texas Health Resources Predictive and Inferential Analysts in Arlington, Texas

Texas Health Resources seeks Predictive and Inferential Analysts for Arlington, TX. Send resume to HR, 612 E. Lamar Blvd., Ste. 400, Arlington, TX 76011 or apply online at www.texashealth.org/careers. EOE.

Predictive and Inferential Analysts: Manipulate and join data from multiple sources into population set for comparative analysis using a SQL or No-SQL tool approaches; deliver actionable insights with data to propose operational or process changes; identify key driver of desired outcomes both known and unknown at the start of the analysis and interpret analytical results for stakeholders; build data sets to be used as training material for models including profiling the data and the knowledge of when to drop data, substitute for missing data, or transform it for better modeling; identify key variables and determine which ones should be dropped; conduct program or project analysis using statistical techniques to prove or disprove efficacy of the projects tying in sources from the EMR, Supply Chain, Finance, Patient Experience, and third-party sources; translate business questions/problems into analytical questions and deliver analytic insights to the business and communicate complex methodologies of analytics to business users; work with the business and IT teams to operationalize AI model into workflows including model management such as model scoring, metric collection, performance monitoring, and restraining the model as necessary; deliver presentations to leadership on findings through graphical displays; and write statistical methodology and results for technical reports and publication.

Education Requirements: Bachelor’s degree in Information Technology, Statistics, Data Science, Analytics or a closely related field.

Work Experience Requirements: Two (2) years of professional work experience in business analysis including SPSS, SAS, R, Spark, and Data Robot or Python or equivalent software; Tableau, Cognos, and Power BI or equivalent visualization software; experience with SQL including to find and aggregate data in a database; and at least one (1) year of experience using AI or machine learning techniques.

Additional Requirements: Undergraduate or graduate academic studies and/or work experience must have included models building using Logistic Regression, Random Forest, K-mean, Bayes Classifier, Decision Trees, and Support vector functions.

Texas Health requires a resume when an application is submitted.Employment opportunities are only reflective of wholly owned Texas Health Resources entities.

We are an Equal Opportunity Employer and do not discriminate against any employees or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state or local protected class.

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