Epidemiology Analyst (Research Analyst I) in Neurosurgery

Working Title: Epidemiology Analyst (Research Analyst I) in Neurosurgery

Occupational Summary

The Ostrom Lab in the Department of Neurosurgery is looking for an experienced research analyst to join our team focused on identifying risk factors for primary and metastatic brain tumors. This role involves providing leadership and expertise in conducting complex research activities, including planning, organizing, conducting, and communicating multiple research epidemiological studies.

This position requires:

* An understanding of core statistical methods and statistical programming for monitoring data quality, modifying and cleaning data for analyses and performing statistical analysis.

* Prior experience with cancer registry data and/or large administrative databases such as Medicare, or Electronic Health record data

* Experience in R programming

* The ability to work independently to perform intermediate and advanced statistical analysis and programming.

* Experience in survival analysis.

* Simultaneous balancing of multiple competing projects and deadlines

* Working in close collaboration with the principal investigator and multi-institutional project teams.

* Interpreting and communicating statistical results and methods.

* Reviewing and editing manuscripts, abstracts, and presentations.

Preferred skills

* Performing complex data management tasks in SAS, R, and/or python.

* Experience in geospatial modeling.

* Experience in analyzing data from genome-wide association studies and related downstream analyses (mendelian randomization, LD score regression).

Work Performed

Project management (30%)

* Lead, coordinate, and perform a variety of complex independent and team activities involved in the collection, analysis, documentation and interpretation of clinical or genomic related information.

* Coordinate the development of research materials and the application of qualitative and quantitative research techniques; write procedures manuals for data collection and coding.

* Establish work procedures; select sources of information and specific data; Prepare correspondence to locate the specific data required.

* Establish work procedures; select sources of information and specific data.

* Train lower-level personnel and peers in research methodology.

* Supervises the work of lower-level employees and trainees engaged in the data analysis.

* Develops leadership and communication skills and shares them with others.

* Is highly organized, with the initiative, and technical aptitude to work with limited supervision.

* Ability to identify problems and solve them pragmatically.

* Manages project responsibilities and takes initiative to complete project-specific responsibilities with minimal supervision.

* Understands the project scope of work and accurately projects to the time and effort needed to complete each phase of project.

* Recognizes when changes to scope will require significantly more effort than allotted and bring this to the attention of the study team.

* Creates timelines for project management independently.

Statistical analysis (40%)

* Evaluates and interprets data and prepares oral presentations or written reports.

* Confer with principal investigator to discuss the interpretation of results and the preparation of manuscripts for publication.

* Perform data management for multiple types of data including, but not limited to, cancer registry data, patient clinical data, environmental exposure data and genetic data.

* Create analytic datasets, combines multiple disparate raw databases and derives analysis variables accurately.

* Prepares statistical analysis plans in collaboration with principal investigator, other lab members, and outside collaborators.

* Research the literature for modern statistical designs and analyses that can be applied to the data and necessary documentation, learns new statistical methods as needed, and applies new skills to future projects.

* Independently generates descriptive and basic test statistics, data analysis and generates statistical modeling results.

Collaboration (20%)

* Collaborates effectively with principal investigator, research group, and internal/external collaborators.

* Identifies potential data problems from analytic queries and brings them to the attention of the team.

* Demonstrates understanding of project data sets and shares knowledge with collaborators.

* Leads statistical aspects of a research project, with consultation or assistance when needed.

* Represents the functional group in project team meetings and contributes constructively to project discussions.

Dissemination (10%)

* Documents analyses, creates summaries, and presents results in written and verbal form to research teams during project meetings.

* Leads analysis and writing without guidance during all phases of manuscript and report development and revision.

* Independently manuscripts submitted to peer-reviewed journals, abstracts, and grants.

Perform other related duties incidental to the work described herein.

The above statements describe the general nature and level of work being performed by individuals assigned to this classification. This is not intended to be an exhaustive list of all responsibilities and duties required of personnel so classified.

Required Qualifications at this Level

Education/Training

Work requires a Bachelor's degree in a field related to the specific position. A Master's degree in Biostatistics, Epidemiology, Public Health, or a related field is strongly preferred.

Experience

Work requires two years of experience in research/data analysis or related position. Prior contribution to analysis of research projects, a working knowledge of R, and solid command of the English language is required. Has knowledge of the core statistical methods including calculating survival, lifetime risk, prevalence and incidence and statistical programming for monitoring data quality, modifying data for analyses (i.e. data management) and performing statistical analysis. Has knowledge of statistical methods for data that includes genetic and environmental exposure information. Experience with cancer registry data is strongly preferred. Familiarity with SAS, SNP array and/or sequencing data management and analysis is beneficial but not required.

How to apply:

Please submit a cover letter describing your prior research experience, including reference to at least one piece of public-facing scientific or public health material (e.g., published or pre-printed manuscript, poster presentation, oral presentation, cancer surveillance reporting, advocacy materials) to which you have made a substantial contribution and/or another example of a leadership role that you have taken in research or public health.