Data Analyst/Manager

EHA is seeking a skilled and experienced Data Analyst/Manager to support the CDC in managing and analyzing complex COVID and RSV hospitalization datasets. The ideal candidate must possess advanced technical expertise in SAS, a strong foundation in statistical methods, and have the ability to work independently while quickly grasping intricate data systems. The candidate will play a pivotal role in performing sophisticated analyses and supporting CDC’s public health surveillance and decision-making objectives.   Required Skills and Qualifications: Advanced Proficiency in SAS for Data Manipulation and Analysis: Demonstrated expertise in using various SAS procedures and syntax to clean, manipulate, transform, and analyze data efficiently. Ability to manage and process large, complex datasets with accuracy and minimal supervision. Application of Advanced Statistical Concepts using SAS: Strong understanding of statistical principles, including regression analysis and mixed-effects models using SAS procedures like PROC LOGISTIC and PROC MIXED. Ability to detect and analyze statistical changes over time, including trends, shifts, and anomalies, using time series methods with SAS. Proficiency with advanced statistical methods such as: Sensitivity analyses to assess robustness of findings under different assumptions Imputation for missing or incomplete data Propensity score adjustment to adjust for confounding Expertise in tailoring statistical models to clinical or hospitalization datasets to identify public health trends and inform decision-making. Proven ability to apply statistical methods to deliver actionable insights that support CDC’s mission of evidence-based public health policy. Expertise in SAS Macros: Proficiency in writing and implementing complex SAS Macros tailored to solve specific analytical problems and automate repetitive tasks to improve efficiency. Familiarity with advanced macro functionalities, such as arrays, local and global macros, and PROC SQL, for optimizing analytical processes. Experience with Analyzing Weighted Data: In-depth knowledge of SAS procedures (e.g., PROC SURVEYFREQ) for analyzing weighted data. Ability to Work with Existing SAS Code: Proficiency in reading and interpreting existing SAS code written by other analysts or teams. Skilled at adapting, troubleshooting, and improving existing SAS programs to enhance performance, accuracy, and functionality. Ability to identify inefficiencies or errors in code and implement improvements while maintaining data integrity. Complex Data Handling: Knowledge of working with messy, incomplete, or inconsistent time series data and employing SAS tools to clean and prepare it for analysis. Preferred Experience with SAS-Callable SUDAAN: Familiarity with SAS-callable SUDAAN for weighted data analysis is preferred, including the ability to implement its syntax and procedures effectively. Familiarity with Clinical or Hospitalization Surveillance Data: Prior experience working with clinical or hospitalization surveillance datasets, including the ability to analyze data specific to health outcomes and epidemiological research. Knowledge of public health surveillance systems and methodologies for analyzing disease trends and outcomes. Documentation and Reproducibility: Strong skills in creating well-documented, modular, and reproducible SAS code for transparency and ease of use by other team members. Advanced Data Visualization Experience with integrating SAS data and outputs into external visualization tools to communicate findings effectively. Bonus Skills: Basic knowledge of Databricks, Python, PySpark, and Power BI, or knowledge of how to integrate SAS with other data systems, such as SQL databases, Python, or R, is a plus. Familiarity with SAS integration with cloud platforms like Azure is a plus.   Additional Requirements: Proven ability to perform analyses independently and deliver high-quality results within tight timelines. Capacity to quickly grasp and adapt to complex datasets, workflows, and project requirements. Strong problem-solving skills with a focus on innovation, efficiency, and attention to detail. Excellent written and verbal communication skills for documenting processes and presenting findings to both technical and non-technical stakeholders.   Responsibilities: Perform data cleaning, manipulation, and advanced statistical analyses using SAS. Develop and optimize SAS Macros to streamline workflows and automate repetitive tasks. Analyze survey (weighted) data using SAS and/or SAS-callable SUDAAN, providing accurate and actionable insights. Collaborate with internal teams to define analytical objectives, troubleshoot technical issues, and ensure delivery of impactful, high-quality solutions. Leverage bonus skills (Databricks, Python, PySpark, and Power BI) to support data workflows and create meaningful visualizations, if applicable.   This is a full-time, salaried position with benefits Location of the job is Remote or on-site in Atlanta, GA   EHA offers a competitive benefits package to include: paid holidays, paid time off including sick and vacation leave, medical, dental and vision insurance, flexible spending accounts, short and long term disability, company paid life insurance, 401(k) with a company match and discretionary profit sharing and tuition reimbursement.