Data Scientist I - 529470

Pay Grade/Pay Range: Minimum: $62,300 - Midpoint: $81,000 (Salaried E10) Department/Organization: 750502 - Global Water Security Center Normal Work Schedule: Monday - Friday 8:00am to 5:00pm Note to Applicants: Position is eligible for remote work subject to University policy. Job Summary: The Data Scientist I assists in data management and integration efforts across the university, state, and federal agencies. Develops processes to extract, transform, and load data into common data repositories. Coordinates creating new databases, performing database backups and restores, user maintenance, and ensuring database performance. Additional Department Summary: Global Water Security Center (GWSC) is a research -to-operations center, this position will be involved in a range of activities from exploratory analysis to development and implementation of data workflow to data visualization and communication. GWSC is also an applied research and operational center commissioned to respond to our nation’s need for water and environmental security insights. GWSC will inform national security partners and others with global interests in water and environmental security. Our partners will include the Department of Defense (DoD), other US Government agencies, private companies, and data producers from federal agencies and academia. Works closely with researchers across a range of disciplines to analyze water, weather, climate, and environmental data to solve water security issues. Continuation in this position is contingent upon availability of external funding derived from research programs or specific projects. Required Minimum Qualifications: Bachelor's degree or higher and some data science or analytics experience. Additional Required Department Minimum Qualifications: Due to requirements of the funding source, must be a U.S. Citizen or U.S. Permanent Resident. Skills and Knowledge: Self-starter, analytically creative, willing to brainstorm, and inquisitive. Experience working with large datasets and conducting statistical analysis. Experience with and understanding of environmental data. Experience managing and analyzing large, multi-dimensional datasets. Experience with statistical analyses. For example: experience with non-normally distributed data and statistical analyses including regressions, t-tests, nonparametric tests, power analyses, multivariate and/or ordination techniques. Demonstrable knowledge in a programming language or languages often applied to environmental datasets; examples could include R, Python, mySQL, MATLAB and JavaScript, or other GIScience. Preferred Qualifications: Bachelor's degree or higher and two (2) years of data science or analytics experience or education and work experience to equal six years. Experience with Bayesian statistics and censored datasets preferred. Background Investigation Statement: Prior to hiring, the final candidate(s) must successfully pass a pre-employment background investigation and information obtained from social media and other internet sources. A prior conviction reported as a result of the background investigation DOES NOT automatically disqualify a candidate from consideration for this position. A candidate with a prior conviction or negative behavioral red flags will receive an individualized review of the prior conviction or negative behavioral red flags before a hiring decision is made. Equal Employment Opportunity: The University of Alabama is an Equal Employment/Equal Educational Opportunity Institution. All qualified applicants will receive consideration for employment or volunteer status without regard to any legally protected basis and will not be discriminated against because of their protected status. Applicants and employees of this institution are protected under Federal law from discrimination on several bases. More information is available in the EEOC’s Know Your Rights: Workplace discrimination is illegal poster. The University of Alabama affirms its longstanding commitment to institutional neutrality, free speech, and academic freedom.