Staff Associate II

We are looking for a candidate to join our research team as a staff associate II. For this full-time officer of research position, we seek a person with strong programming, data management, analytic, and communication skills to join our team in the assessment of national claims data, clinical registry data, and disease simulation modeling to evaluate drivers of outcomes, quality, and value for patients with cancer. The larger mission and goal of the research group is to conduct health outcomes research to guide the development, evaluation and utilization of cancer screening, prevention and treatment.

The staff associate’s primary job responsibilities will include the analysis of large-scale datasets and the development of disease simulation model. We seek candidates with a strong background in a quantitative field in public health (epidemiology, statistics, health policy). As a part of this work, a strong foundation in programming is essential.

We are looking for a person with experience and graduate training related to health services research, biostatistics and epidemiology. The ideal candidate will have had some experience working with health administrating/insurance claims data and/or electronic health records. While the position requires technical skills, we are particularly looking for a person passionate about for making the health system work more efficiently and effectively for patients with cancer and in growing as a member of our team.  The research scientist will work closely with a multidisciplinary team of physicians, clinical researchers, epidemiologists, and statisticians. Hence the ability to work well in teams and communicate effectively are paramount.

·       Working directly with the PI to design and implement new projects and to make sure analyses are useful, accurate, and clearly communicated.

·       Merging, cleaning, documenting, and managing administrative and clinical registry-based datasets; analyzing data quality and integrity; identifying and solving data quality problems; coding and creating new variables; preparing analysis files; producing statistical summaries, charts and tables; and communicating results.

·       Perform statistical analyses according to the study design (e.g., hierarchical modeling, survival analyses, weighted analyses, difference-in-difference, simulation, etc.

·       Development and validation of simulation models, including Markov models, to examine effectiveness of treatments in cancer patients.

·       Assist in writing and editing manuscripts for publication.

·       Clearly communicate processes used and results achieved, and suggest new and alternative approaches.

·       Cultivate deep familiarity with methodological approaches and data

·       No prior knowledge of clinical oncology is required, but a desire to learn and to join a team aimed at improving quality and value of care is essential.