The Cancer Prevention & Control Platform ("Platform") accelerates the development, dissemination, and amplification of evidence-based strategies, community services, policy interventions, and knowledge targeting measurable reductions in cancer incidence and mortality at a population level. The Platform represents MD Anderson's primary, focused activation of expertise in the science of public health practice, community-based dissemination of evidence-based practices, applied implementation science, and impact measurement for community-facing initiatives.
To reduce the risk of cancer, it is critical to empower community-based organizations - such as schools, community colleges, non-profit organizations, workplaces, government agencies and policymakers - with evidence-based interventions, especially in communities with limited resources. The Platform leads significant place-based initiatives working with more than 50 local, regional, and state organizations to deliver evidence-based interventions in cancer prevention and control
The primary purpose of the Data Analytics Specialist, Geospatial Analysis position is to carry out spatial data analysis to create and maintain complex GIS data and/or maps, and other applications to support the management and administration of the Platform's projects. This role coordinates with and provides GIS support to, the research, program implementation, and collaborating organization staff. Additional roles of the data analyst include but not limited to: perform GIS data creation, maintenance, conversion, and quality assurance/quality control activities; extract relevant information from the gathered geospatial data and apply analytical methods to solve problems; manage geospatial data into various data sets to suit the needs of programs and collaborating organizations; prepare written reports, manuscripts and grant application with investigators. This position will have the opportunity to participate in multiple research and practice projects involving study design and implement, data collection, statistical analysis and publication.
The ideal candidate will have a strong spatial analysis and statistical background and be able to demonstrate skills in geospatial reporting and data visualization using tools such as ArcGIS Online/Pro and/or other geospatial software and programming languages. This position will work closely with the entire Platform Team, The University of Texas Health and Science Center: School of Public health as well as other collaborating organizations. This position will work closely with the entire Platform Team, the Impact Evaluation Core and contributes to a strong team environment and fosters inclusivity.
Required: Bachelor's degree in Business Administration, Statistic, Healthcare Administration or related field.
Required: Five years' experience in data analysis. With preferred degree, three years' experience in data analysis.
Preferred: E xperience with geospatial data informatics management, mainframe and/or PC databases, document processing, statistical consulting and analysis, program impact evaluation and statistical software. Additional experience with public health and health care data, health data informatics management and data analysis with extensive experience with geospatial datasets. Evidence of scientific writing and publication is a plus. Demonstrated ability to work effectively in a collaborative environment. Ability to work in a fast-paced environment, under pressure. Willing and able to work extended and flexible hours, function under demanding circumstances.
It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state or local laws unless such distinction is required by law. http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html