Statistical Analyst

Responsibilities

• We are seeking a data science analyst/ biostatistician to use data science tools and methodologies to identify and analyze real-world healthcare data for scientific research in precision medicine.
• You will work in a highly collaborative environment, closely collaborating with American Heart Association scientists, clinical and research volunteers, and program managers to creatively solve challenges in medical research using state-of-the-art tools and methodologies.
• Conduct statistical analysis using clinical registry and electronic health record (EHR) data to address research questions related to cardiovascular disease.
• Collaborate with senior analysts, clinicians, and research teams to refine research questions and develop statistical analysis plans (SAPs).
• Apply and develop traditional and advanced analytical methods, including machine learning, deep learning, and other AI-driven techniques.
• Utilize AI-assisted tools to facilitate code review and maintain rigorous standards for reproducibility and transparency.
• Prepare summary reports, manuscripts, and visualizations for internal and external dissemination.
• Contribute to the preparation of peer-reviewed journal articles and presentations for scientific meetings.
• Serve as a technical/topical expert, champion, consultant, and liaison to Association stakeholders and external peers.
• Attend relevant external conferences, and attend/co-lead consultative sessions with volunteer Task Force and other Association volunteers/experts.
• Contribute landscape and topical expertise to the development and execution of comms plan/strategies, including networks to engage, written pieces, workshop planning, and publication strategies.

Qualifications

• Master’s or PhD degree in data science, biostatistics, biomedical informatics, computer science, statistics, public health, epidemiology, applied mathematics, or a related field.
• Minimum of 3 years of experience with R or Python for statistical computing and data analysis.
• Experience in preprocessing and modeling clinical data, especially patient-level data from EHRs or registries.
• Experience in both traditional statistical modeling and machine learning techniques.
• Minimum of 2 years of experience analyzing real-world patient data in clinical or research settings.
• Experience writing and executing Statistical Analysis Plans.
• Strong skills in managing and analyzing large-scale, complex clinical datasets.
• Excellent oral and written communication skills, with the ability to effectively communicate technical/statistical information to both technical and non-technical stakeholders.
• Highly effective organizational skills, time management, responsibility, and motivation.
• Ability to travel up to 10%, including occasional overnight stays.

Preferred Experience

• Python programming language.
• Cardiovascular Data Analysis.
• Experience working in a healthcare or research environment.