Statistician

Job Description:

• The statistician will assist the Childhood Lead Poisoning Prevention Program update the lead risk map using housing data, poverty level, demographic characteristics, and the number of children with elevated blood lead levels.
• The statistician will also train the lead surveillance epi and create an SOP to enhance CLPPP program capacity.
• The statistician will combine information on testing rates and lead exposure risk to identify where and how these two factors overlap in geographic space to create a targeted lead outreach map that can be used to prioritize areas for increased testing for lead, for example, by identifying census tracts with high exposure risk and low testing rates.
• The statistician will evaluate the childhood and adult blood lead databases to determine the relationship and possible take-home exposures.

Skills Required:

• Skills in statistical analysis, systems programming, database design, and data security measures.
• Skills in a wide range of analyses such as hierarchical linear models, survival analysis, propensity score estimation, random forests Skills in communicating complex information clearly and concisely, both verbally and in writing.
• Skills in identifying code or data issues and finding solutions.
• Skills in writing, testing, and implementing programs using SAS/Python/R to clean, manage, merge, and analyze large datasets.
• Skills in summarizing, interpreting, and presenting results in written, tabular, and visual formats for reports, manuscripts, and presentations Time management skills.
• Ability to write clear and concise analytical documentation, summaries of various methodologies, and descriptions of statistical results, as well as create charts, tables, and other visual aids.
• Ability to work in a fast-paced environment, handle multiple projects simultaneously, set priorities, and take initiative while informing supervisors and project leads.
• Ability to work effectively with limited supervision

Experience Required

• Demonstrate experience performing moderately complex statistical programming.
• Demonstrate working experience with statistical methods and models incorporating various variable types and traditional and modern statistical approaches.
• Demonstrate knowledge of statistical computer packages.
• Demonstrate knowledge of Windows PCs and familiarity with the MAC platform.
• Demonstrated knowledge of Word, Excel, PowerPoint, and relational database concepts
• Three or more years of experience in data management and statistical analysis.
• Experience with complex data structures and linkages between data sources.