Additionalinformation

Additional Information

• Appointment End Date: One year from date of hire
• Standard Hours/Schedule: 35 hours per week
• Visa Sponsorship Information: Harvard University is unable to provide visa sponsorship for this position
• Pre-Employment Screening: Identity, Education, Criminal

Join the Harvard T.H. Chan School of Public Health to support our mission of health research and education, and to be a part of the oldest institution of higher learning in the country!

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• The Harvard T.H. Chan School of Public Health does not provide visa sponsorship, now or in the future, for staff positions.
• Harvard University requires pre-employment reference checks and background screenings.
• This position has a 90 day orientation and review period.

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The health of our workforce is a priority for Harvard University. With that in mind, we strongly encourage all employees to be up to date on CDC-recommended vaccines.

Work Format Details

This position has been determined by school or unit leaders that some of the duties and responsibilities can be effectively performed at a non-Harvard location. The work schedule and location will be set by the department at its discretion and based upon operational needs. When not working at a Harvard or Harvard-designated location, employees in hybrid positions must work in a Harvard registered state in compliance with the University’s Policy on Employment Outside of Massachusetts. Additional details will be discussed during the interview process. Certain visa types and funding sources may limit work location. Individuals must meet work location sponsorship requirements prior to employment.

Salary Grade and Ranges

This position is salary grade level 056. Please visit Harvard's Salary Ranges to view the corresponding salary range and related information.

Benefits

Harvard offers a comprehensive benefits package that is designed to support a healthy work-life balance and your physical, mental and financial wellbeing. Because here, you are what matters. Our benefits include, but are not limited to:

• Generous paid time off including parental leave
• Medical, dental, and vision health insurance coverage starting on day one
• Retirement plans with university contributions
• Wellbeing and mental health resources
• Support for families and caregivers
• Professional development opportunities including tuition assistance and reimbursement
• Commuter benefits, discounts and campus perks

Learn more about these and additional benefits on our Benefits & Wellbeing Page.

EEO/Non-Discrimination Commitment Statement

Harvard University is committed to equal opportunity and non-discrimination. We seek talent from all parts of society and the world, and we strive to ensure everyone at Harvard thrives. Our differences help our community advance Harvard's academic purposes.

Harvard has an equal employment opportunity policy that outlines our commitment to prohibiting discrimination on the basis of race, ethnicity, color, national origin, sex, sexual orientation, gender identity, veteran status, religion, disability, or any other characteristic protected by law or identified in the university's non-discrimination policy. Harvard's equal employment opportunity policy and non-discrimination policy help all community members participate fully in work and campus life free from harassment and discrimination.

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Company Description

By working at Harvard University, you join a vibrant community that advances Harvard's world-changing mission in meaningful ways, inspires innovation and collaboration, and builds skills and expertise. We are dedicated to creating a diverse and welcoming environment where everyone can thrive.

Why join the Harvard T.H. Chan School of Public Health?

The Harvard T.H. Chan School of Public Health is a world-renowned institution dedicated to advancing public health through cutting-edge research, education, and global collaboration. Our school is a special place to work because of its vibrant, mission-driven community, interdisciplinary approach, and commitment to addressing some of the most pressing health challenges worldwide. We foster a collaborative and inclusive work environment where innovation, continuous learning, and work-life balance are valued.

Learn more about the School’s mission, objectives, and core values, our Principles of Citizenship, and about the Dean’s AAA vision about our school’s ongoing strategic initiatives.

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Job Description

Job Summary:

The Department of Epidemiology, at the Harvard T.H. Chan School of Public Health, studies the frequency, distribution, and determinants of disease in humans, a fundamental science of public health. In addition to pursuing ground-breaking global research initiatives, we educate and prepare future medical leaders and practitioners as part of our mission to ignite positive changes in the quality of health across the world.

CAUSALab (within the Department of Epidemiology) conducts cutting edge research using large health care databases to determine what works. The investigators within the CAUSALab have obtained uninterrupted funding for their teams for more than 20 years. Currently this includes projects in HIV, cancer, cardiovascular diseases, COVID-19, pregnancy and methodological applications of causal inference and artificial intelligence. Results from studies have informed guidelines for the treatment and prevention of multiple diseases, and contributed to the innovation of methods to generate valid evidence from real world data. The candidate will join a core team comprised of another Senior Programmer and two Programmers.

CAUSALab is seeking a full-time SAS Programmer to support a research team of faculty members (principal investigators Alejandro Szmulewicz, Sara Lodi and Miguel Hernán), postdoctoral researchers, students, and external collaborators. The Programmer will be responsible for the management of healthcare databases and other complex databases, as well as for the documentation of code.

Job-Specific Responsibilities:

• Job duties and responsibilities include, but are not limited to, the following:
• Develop and deploy data cleaning, data management, variable creation, and variable naming protocols of projects involving electronic health records, administrative claims, and other complex databases
• Create and maintain databases using SAS and SQL in collaboration with members of the research team
• Create and link customized databases and analytic datasets in UNIX and Windows environments
• Assist with the maintenance and documentation of software in SAS and SQL
• Function as a resource for researchers, post-docs and other trainees to help debug programs and to access correct data
• Performs other duties as assigned

PLEASE NOTE: This position is grant-funded and only a U.S. Citizen can be considered.

PLEASE NOTE: This position has a term appointment of one year from the date of hire with possibility of extension.

PLEASE NOTE: Short-listed candidates will be required to submit work samples (sample code) and/or complete a coding assessment.

PLEASE NOTE: Finalist will be required to complete a background screening process for the US Veterans Administration.

Qualifications

Basic Qualifications:

• Minimum of two years’ post-secondary education or relevant work experience
• Professional statistical programming experience using SQL & SAS is required

Additional Qualifications and Skills:

• Bachelor's degree, preferably in biostatistics, statistics or computer science
• Master’s Degree preferred in Public Health Domain, Statistics, Data Science, Computer Science, Mathematics, Informatics, or other health data related field
• Minimum of 2+ years statistical programming experience required (if have Master's degree)
• Minimum of 3+ years of statistical programming experience required (if have Bachelor's degree)
• Proficiency with Microsoft Office tools
• Experience in working with big data and independently building analytic databases
• Working knowledge of data analysis
• Basic knowledge of study design, research methodology
• Understanding of the healthcare domain, clinical, epidemiology and/or genomic data is a plus
• Natural Language Processing language is a plus
• Directly-related, practical experience in SAS and SQL, an engineering-like mindset, be mathematically oriented, and enjoy writing code for large and complex datasets
• Excellent written, verbal, and interpersonal communication skills
• Highly organized with a strong attention to detail and accuracy
• Experience collaborating with all levels of research team; demonstrated team performance skills
• Service-oriented mindset and approach