GENERAL SUMMARY/ OVERVIEW STATEMENT:

The Medical Practice Evaluation Center (MPEC) has an opportunity for an enthusiastic and energetic individual to join our research team investigating the clinical and economic value of alternative strategies of HIV treatment and prevention, as well as modeling other diseases. The position is with an internationally-recognized, multidisciplinary team from Massachusetts General Hospital, Harvard Medical School, Harvard T.H. Chan School of Public Health, Yale School of Medicine, Brigham and Women’s Hospital, and multiple international institutions. Together, the group studies the clinical impact and cost-effectiveness of various HIV/AIDS, tuberculosis, tobacco, diabetes, cardiovascular, and other disease prevention and treatment options in collaboration with researchers domestically in the US, as well as in several countries, including Botswana, Brazil, Côte d’Ivoire, France, India, Mozambique, South Africa, Thailand, and Zimbabwe.

The candidate should be highly motivated with experience in quantitative methods and public health research. The candidate should have solid foundation in biostatistics and statistical programming. Ideally, the candidate will have experience in mathematical model development, parameterization, and debugging. The position offers a stimulating, collaborative, and multidisciplinary environment and the opportunity to contribute to the development of the NIH-funded Cost-effectiveness of Preventing AIDS Complications (“CEPAC”) model and potentially other disease models. The primary responsibilities of this individual will be to help design and then conduct model-based cost-effectiveness analyses, lead in abstract presentation and manuscript preparation, assist with model refinement and expansion, and assist with new proposals and grant preparation. There are multiple possibilities for collaboration with other researchers in Boston, as well as with many national and international research groups and institutions.

Interested candidates should apply via www.massgeneral.org/careers. (Job ID # 3129496)

The Medical Practice Evaluation Center is posting two separate data analyst positions. Please see Job ID # 3129494 and if you would like to be considered for both roles, you may note this in your cover letter.

**When applying, please upload a cover letter, resume, undergraduate and graduate transcripts (unofficial transcript is OK). Applications that do not include all components will NOT be considered.**

For more information regarding our group, please visit http://mpec.massgeneral.org/.

PRINCIPAL DUTIES AND RESPONSIBILITIES:

Responsibilities include, but are not limited to, the following activities:

· Communicate with clinical investigators to understand scientific issues, determine appropriate statistical analyses, and describe results

· Work with the study team and senior statisticians to develop reporting and quality control plans

· Use SAS to generate reports on study progress

· Develop programs to perform complete data validation and error detection, ensuring that all are informed of any issues relating to data integrity

· Perform literature reviews of the relevant statistical methods used in data analyses

· Provide senior statisticians with data requests and sample pull lists for Principal Investigators

· Perform statistical analysis of data

· Assist in manuscript preparation

· Assist in design of interventional studies and analysis plans for external data sets

· Attend team meetings within MPEC

QUALIFICATIONS:

Qualifications include the following:

• Master’s degree in Biostatistics or Statistics, with a strong background and demonstrated ability in quantitative analysis and statistics

• At least 6 months of experience programming, preferably in SAS®, which might be gained from coursework

SKILLS/ ABILITIES/ COMPETENCIES REQUIRED:

• Capacity to manipulate and organize large amounts of data

• Excellent communication skills, as much of the incumbent’s work will be summarized in written reports to investigators

• Organization, efficiency, and attention to detail

• Facility with SAS and ACCESS data and R, python or other statistical software

• Ability to work both independently and as part of a team and to collaborate with team members located remotely

• Proficiency with standard office software (Microsoft Word, Excel, and PowerPoint as well as Internet applications) and the ability to learn new computer applications

• Ability to handle multiple tasks and deadline pressures

• Intellectual independence and initiative

This description has been designed to indicate the general nature and level of work performed by an employee within this position. The actual duties, responsibilities and qualifications may vary based on need.

SKILLS/ ABILITIES/ COMPETENCIES HIGHLY DESIRABLE :

• Ability to work with mathematical models, such as Markov and Monte Carlo simulation models, as well as compartmental and agent-based epidemiological models, experience in deterministic and probabilistic sensitivity analysis, and ability to solve technical problems in these areas

• Previous public health or international healthcare research experience preferred

WORKING CONDITIONS:

Duties will be carried out in a typical office environment (can be performed remotely during the COVID-19 pandemic). Occasional evening or weekend work may be required.

SUPERVISORY RESPONSIBILITY:

None.

EQUAL OPPORTUNITY EMPLOYER:

In keeping with our overarching mission to reduce health and other disparities in vulnerable populations, the Medical Practice Evaluation Center is specifically committed to recruiting a diverse team of individuals across race, ethnicity, sexual orientation, and ability backgrounds to ensure that our science is informed by and responsive to the communities we aim to serve. The Center strives to become a leader in developing and maintaining increased representation, recognition, and support of each of these dimensions of diversity among all of its members.

The above is intended to describe the general contents and requirements of work being performed by people assigned to this classification. It is not intended to be construed as an exhaustive statement of all duties, responsibilities or skills of personnel