Research Data Manager At Muso

Location: Bamako, Mali

Department of Research Monitoring & Evaluation

Full-time

Supervised by: Research Senior Manager

About Muso:

Muso believes no one should die waiting for health care. That’s why we’ve set out to create a cure for delay. We build health systems to save lives by reaching patients faster, within hours of the moment they become sick. To do this, we partner with communities facing extreme poverty.

Muso has spent more than a decade creating and improving our Proactive Care model, preparing it to serve the global effort for universal health care. We have documented rapid health improvements across the populations we serve: a 2018 study found that communities we serve in Mali, which previously saw some of the world’s highest child mortality rates, sustained child mortality rates lower than any country in sub-Saharan Africa for five years, and ultimately reached a rate on par with that of the United States. Patient access to care increased tenfold. Muso now serves the governments of Mali and Cote d’Ivoire in their efforts to translate the results of this research into national policy and practice.

We provide proactive health care to 350,000 patients in peri-urban and rural Mali, and embed rigorous academic research and strategic advocacy to identify and share strategies that can accelerate global efforts for child survival, maternal health, and universal health care. Given the transformations in health care access and survival Muso has documented, over the next five years our direct service, research, and advocacy will work to advance a new global model for health care. Learn more about our work at www.musohealth.org.

About the role:

Through rigorous research activities with its academic collaborators, Muso helps national and international partners to promote universal access to healthcare. This role will help the department achieve its objectives by ensuring data collection completeness and quality, performing data management and preparation for analysis, and conducting rigorous analysis for research studies. Under the supervision of the Senior Research Manager (SRM), the Research Data Manager (RDM) will supervise a team of Data Managers (DMs), providing in-depth code review, assuring the quality of data management activities, and overseeing real-time quality control on study data. They will also ensure that appropriate validation is embedded in data collection tools. Beyond being responsible for ensuring the quality of research data sources, the RDM will apply statistical methods to support health research. This includes preparing research datasets, conducting high-quality bio-statistical analyses to answer research questions, and assisting with the development of research protocols and statistical analysis plans.

Responsibilities:

• Supervise activities related to data management and quality control of research data sources
• Supervise the creation of data dictionaries and other documentation
• Review code written by DMs for clarity and accuracy, and help DMs improve Stata and SQL skills
• Provide technical assistance to other teams with issues of data quality, merging and de-duplication, and analysis of surveys
• Serve as Project Manager and Supervisor for the Data Management team
• Manages and supports the DM team
• Work with the DMs on daily data management tasks: data collection, follow-up planning, quality control and follow-up of investigators’ activities
• Hold regular project management meetings to set priorities, communicate deadlines, and address issues
• Clearly communicate team priorities and capacities to departmental leadership and other internal stakeholders
• Help develop data management strategy for Muso
• Assist the Data Operations and Training Manager (DOTM) with skills-based trainings on technical tools related to data management, and recommend new tools as needed.
• Proactively develop and implement data management protocols and best practices
• Communicate with external collaborators and other Muso departments about research data quality concerns
• Support the design of data collection tools and systems
• Implement procedures to review data collection tool design
• Help develop skip logic, validation measures, and other features of survey tools
• Support DMs as they perform quality control on collected data to improve ongoing data collection efforts
• Respond to requests for data and analytical products
• Work with internal and external collaborators to supply research study data needed for funders, reports, analyses, and programmatic purposes
• Participates in data analysis and the preparation of research project reports, publications, final reports and presentations
• Help with archiving study databases and related documents as required
• Conduct statistical analyses to further research objectives
• Oversee the preparation of research datasets for analysis
• Conduct statistical analyses according to research study protocols and plans
• Author statistical analysis and data management plans to meet research objectives

You Need to Have :

• Master’s degree in public health, epidemiology, statistics, demography, or a related field with 2 years of work experience in a similar role, or a Bachelor’s degree with 4 years of work experience in a similar role. In particular, work experience cleaning, managing, preparing data for a randomized controlled trial, non-randomized controlled trial, controlled before-and-after study, interrupted time series, or repeated measures study evaluating the effects of healthcare interventions.
• Knowledge of research methodology and data procedures for such studies , including good clinical practice, survey methodology, medical terminology, informatics, data protection and reporting formats.
• Proven ability to independently produce a high-quality, well-organized and well-documented script (preferably in Stata) to conduct QAQC, prepare, and analyze health research study data, including descriptive analyses, basic significance testing, and regression models.
• Ability to translate requirements from a statistical analysis plan (or a conversation with a principal investigator) into functioning code that achieves this task. Candidate should be able to accomplish this type of cleaning and re-coding operation in at least one statistical analysis package, such as SPSS, SAS, Stata, MATLAB, R or Python. The candidate should be able and willing to learn and use advanced Stata skills on the job if hired.
• Ability to summarize analytical findings and data quality issues in a professional report, using data displays such as tables, figures, and other supporting visualizations where necessary.
• Experience in modern software and web-based computer systems, including Google products such as Gmail, Google Sheets, and Google Docs.
• Experience using and programming electronic data collection tools, such as Google Forms, Open Data Kit, Open Clinica, Kobo Collect or RedCap.
• Excellent written and verbal communication and listening skills in French.
• Ability to read, comprehend, and respond to written material in English.
• Meticulous attention to detail
• Experience leading or managing a team in order to set and meet deadlines and achieve goals.
• Ability to lead decisively while also listening to diverse perspectives
• Sense of accountability and responsibility for projects with shared ownership
• Experience in juggling conflicting short-term priorities while not losing sight of long-term goals

You Will Impress Us If You Have :

• Project management experience, or the demonstrated ability to coordinate multiple projects and conflicting priorities while communicating in a precise and effective manner.
• Experience working with diverse, international organizations across countries and timezones.
• Ability to analyse longitudinal data from cluster randomized trials or complex surveys.
• Knowledge of how to use SQL to query relational databases.
• Knowledge of statistical programming methods in R or Python.
• Experience in GitHub or other collaboration software.
• Professional experience as a supervisor or team leader, preferably in a data management or data analysis context.
• Strong written and oral English language skills.