Mount Sinai Careers
Biostatistician I, Environmental Medicine and Public Health
Ground breaking science. Advancing medicine. Healing made personal.
We are looking for a highly motivated biostatistical programmer with interests in big-data analysis and environmental health research to join Dr. Colicino’s research team at the Icahn School of Medicine at Mount Sinai. The team focuses on developing and applying novel statistical methods in environmental epidemiologic studies, with specific attention to high dimensional molecular biomarkers (e.g. epigenomics). The research team is based in the department of Environmental Medicine and Public Health, which is leader in environmental public health research and located next to Central Park in Manhattan’s Upper East Side.
This position may fit a candidate with strong quantitative background seeking additional experience in data science. The candidate will carry out large-scale statistical analyses, will assist in the scientific manuscripts preparation and will collaborate with scientists with different background. Expertise with the R programming language is required, and experience with high performance computing approaches is highly desirable. Excellent communication and organizational skills are required.
- Conduct reproducible statistical analyses in the R language, including cleaning and managing project files
- Conduct and document analyses using tools for reproducible research (e.g. git, github)
- Assist in descriptive, exploratory, and systematic analyses of diverse types of data
- Assist in manuscript preparation with the possibility of co-authorship on scientific publications
- Assist and advise group members on biostatistical approaches
- Participate in research group meetings, including presenting summaries of ongoing analyses
- Assist in developing R packages to extend computational methods
- Remain informed of new developments in statistical programming that relate to the research program
- Perform other related duties
- Education: Master’s degree in biostatistics, computational biology or related
- Experience: 1 year of biostatistics or related experience in clinical research preferred
- Advanced level of experience in SAS, R or similar application
- Excellent written, oral and interpersonal skills
- Demonstrated analytical and problem solving skills
- Excellent organizational skills
The Mount Sinai Health System believes that diversity and inclusion is a driver for excellence. We share a common devotion to delivering exceptional patient care. Yet we’re as diverse as the city we call home- culturally, ethically, in outlook and lifestyle. When you join us, you become a part of Mount Sinai’s unrivaled record of achievement, education and advancement as we revolutionize healthcare delivery together.
We work hard to recruit and retain the best people, and to create a welcoming, nurturing work environment where you have the opportunity and support to develop professionally. We share the belief that all employees, regardless of job title or expertise, have an impact on quality patient care.
Explore more about this opportunity and how you can help us write a new chapter in our story!
Over 38,000 employees strong, the mission of the Mount Sinai Health System is to provide compassionate patient care with seamless coordination and to advance medicine through unrivaled education, research, and outreach in the many diverse communities we serve.
Formed in September 2013, The Mount Sinai Health System combines the excellence of the Icahn School of Medicine at Mount Sinai with seven premier hospitals, including Mount Sinai Beth Israel, Mount Sinai Brooklyn, The Mount Sinai Hospital, Mount Sinai Queens, Mount Sinai West (formerly Mount Sinai Roosevelt), Mount Sinai St. Luke’s, and New York Eye and Ear Infirmary of Mount Sinai.
The Mount Sinai Health System is an equal opportunity employer. We promote recognition and respect for individual and cultural differences, and we work to make our employees feel valued and appreciated, whatever their race, gender, background, or sexual orientation.