Biostatistician at ICAP Columbia University

Key Responsibilities:

• Statistical Analysis: Design and conduct statistical analyses on biological and clinical datasets, including data from public health surveillance and clinical programs, epidemiological studies, and laboratory results.
• Reporting: Work independently or with the ICAP Data, SI and Informatics teams to prepare detailed reports, presentations, and visualizations of statistical findings for internal and external stakeholders.
• Data Demand & Information Use: Identify and create demand for data and statistical insights within ICAP and public health stakeholders. Develop strategies to leverage statistical information effectively to drive decision-making and operational improvements.
• Data Management: Manage and preprocess data to ensure quality and consistency, including data cleaning, validation, and transformation.
• Model Development: Develop and validate statistical models and algorithms to address public health questions and hypotheses.
• Team Supervision & Mentorship: Oversee and mentor a data team, including the Strategic Information Officer, Data Manager, and Data Officers. Provide guidance on best practices in data management, analysis, and interpretation. Foster a collaborative and supportive environment to enhance team performance and professional growth.
• Collaboration: Work closely with researchers, scientists, and other team members to understand project objectives and provide statistical expertise and guidance.
• Methodology: Stay updated with the latest statistical methodologies and tools to enhance the accuracy and efficiency of analyses.
• Compliance: Ensure adherence to regulatory and ethical standards in statistical practices and data handling.

Qualifications:

• Education: Bachelor's degree in statistics, mathematics, biology, or a related field and Masters in Biostatistics, Statistics, Mathematics, or a related field is an added advantage.
• Experience: Proven experience (typically 3+ years) in a biostatistics or statistical analysis role, preferably in a healthcare, or research setting. Experience in a supervisory or leadership role is highly desirable.
• Technical Skills: Proficiency in statistical software and programming languages such as R, SAS, Python, or SPSS. Experience with data visualization tools (e.g., Tableau, PowerBI and/or Superset) is a plus.
• Analytical Skills: Strong analytical and problem-solving skills with the ability to interpret complex data and draw actionable insights.
• Leadership Skills: Demonstrated ability to lead and mentor a team, with excellent interpersonal and communication skills.
• Communication: Excellent verbal and written communication skills with the ability to present complex statistical concepts to non-statistical audiences.
• Attention to Detail: High level of accuracy and attention to detail in statistical analysis and data handling.