Job Description

Assistant Research Scientist (Data Scientist)

Full-Time

Dr. Aouizerat's laboratory focuses on the identification of molecular mechanisms that underlie symptoms (e.g., pain, fatigue), sequelae (e.g., lymphedema, neuropathy) and treatment (i.e., pharmacogenomics, pharmacokinetics) of common chronic diseases (e.g., cancer, cardiovascular disease, HIV). Research topics include development of epigenomic risk profiles, leveraging publically available datasets to complement de novo cohorts, translational research (i.e., study of targets in humans and mice), genomics (i.e., array-based and sequencing-based), transcriptomics (i.e., array-based and sequencing-based), and functional analyses (e.g., wet bench experiments). The Aouizerat Laboratory works closely with another laboratory with expertise in animal and cell models to permit accelerated translation of processes of interest identified in human data.

The Biostatistician will analyze and manipulate data generated from both internal and external sources, use, modify, or create analysis plans, pipelines and reporting software, and collaborate with other scientists in the group with a variety of analytic (biostatistical) tasks. By applying a variety of software and technologies, the Biostatistician enables the rapid, incremental analysis required to best process and interpret the large amount of data generated in a molecular epidemiology laboratory.

JOB SPECIFIC TASKS

• Develop analytical pipelines for manipulating genomics datasets and interpret results appropriately to ensure accuracy and reliability of those pipelines.
• Collaborate with others in the research team, including statisticians, molecular biologists, molecular epidemiologists, genomic analysts, and other Biostatisticians to design studies and implement computational applications.
• Assist Dr. Aouizerat with design and conduct of research projects.
• Acquire, update and analyze data from internal (e.g., Aouizerat or affiliated laboratories, Genomic Core Facilities) or external (e.g., TCGA, UCSC Genome Browser, 1000Genomes, dbGaP) sources, document system changes, write and maintain documentation for end users. Prepare and contribute to research papers.
• Determine optimal storage environments; advise and collaborate with IT infrastructure colleagues in implementing, tuning and monitoring systems supporting scientific data lifecycle.
• Other duties as assigned.

In compliance with NYC?s Pay Transparency Act, the annual base salary range for this position is $59,000 - $76,000. New York University considers factors such as (but not limited to) the specific grant funding and the terms of the research grant when extending an offer.

Education and Experience:

• Bachelors degree in biology, chemistry or other life sciences
• Master?s in Statistics, PhD preferred
• Experience with biostatistics software; experience in the use of Stata or R preferred
• Experience with multiple programming languages and computational environments, including UNIX-style operating systems, command line interfaces, R, perl/python or similar, and SQL or other database software preferred
• Training in bioinformatics (e.g., Minor, Master?s Degree) preferred
• Background in statistics and quantitative data analysis, as demonstrated through previous work or academic experience preferred
• Experience with and knowledge of biological sciences; genetics and molecular biology preferred
• Experience with project data management preferred.
• Training in data sciences preferred

Required Skills:

• Hands-on experience with a broad spectrum of biostatistical analyses (i.e., regression, GEE, propensity scores, imputation, factor analysis, principal component analysis)
• Excellent programming skills and ability to manipulate large data sets and proficient with design and use of modern relational/non-relational databases.
• Expertise with biostatistical software (i.e., Stata, R, MatLab)
• Experience with relevant biostatistical analysis tools/best practices. 
• Develop, improve, modify, and execute data analysis plans.
• Use or implement current open source software in conducting data analysis at basic and advanced levels.
• Strong analytical and problem-solving skills.
• Ability to document work performed, especially in support of publishing scientific results 
• Excellent communication skills and ability to work with others to accomplish goals.
• Develop and maintain effective working relationships with researchers at all levels; and work closely with Dr. Aouizerat to conduct custom bioinformatic analyses.
• Able to work independently, and as part of a team. 

Desired Skill:

• Excellent oral and presentation skills.
• Experience in bioinformatics applications and next-generation sequence data analysis
• Machine learning approaches
• Latent variable modeling approaches and software (MPlus)
• Knowledge, background, or experience in molecular biology and microbiology. 
• The successful candidate will be able to prioritize and balance multiple projects to meet timelines. 
• Experience in working in a Linux/UNIX environment and experience with cluster computing.
• Excellent oral and presentation skills.

PHYSICAL REQUIREMENTS AND ENVIRONMENTAL CONDITIONS

The physical requirements and environmental conditions of this position consist primarily of:

• Continuous mental and visual attention, requiring sustained attention and observation
• Ability to work at a PC monitor for most of the work day

Applicants should submit: 1) Cover letter; 2) Curriculum Vitae; and 3) Names and contact information of at least two professional references. To access the application, please click the "Apply Now" button located on the right.

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NYU is an Equal Opportunity Employer and is committed to a policy of equal treatment and opportunity in every aspect of its recruitment and hiring process without regard to age, alienage, caregiver status, childbirth, citizenship status, color, creed, disability, domestic violence victim status, ethnicity, familial status, gender and/or gender identity or expression, marital status, military status, national origin, parental status, partnership status, predisposing genetic characteristics, pregnancy, race, religion, reproductive health decision making, sex, sexual orientation, unemployment status, veteran status, or any other legally protected basis. Women, racial and ethnic minorities, persons of minority sexual orientation or gender identity, individuals with disabilities, and veterans are encouraged to apply for vacant positions at all levels.

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