Company Description
QC Medica is a specialized research consultancy focused on Clinical Outcome Assessments (COAs) and patient-centered evidence generation for the life sciences industry. The company partners with pharmaceutical and medical technology organizations to develop and implement Patient-Reported Outcomes (PROs) and other patient experience data, along with COA strategy, instrument development and validation, health-state utility studies, preference research, and qualitative research.
Role Description
This is a contract, remote role for a Consultant Data Scientist / Health Econometrician. The Consultant will apply data science and statistical methodologies to analyze healthcare and economic data supporting COA research, real-world evidence (RWE) generation, and patient-centered outcomes research. The role involves collaborating with interdisciplinary research teams to conduct analyses, develop models, and generate insights that inform health economic evaluation, market access strategies, and HTA submissions.
Key Responsibilities
- Conduct COA and Real-World Evidence (RWE) analyses using healthcare datasets, including electronic health records (EHR) and PRO and other COA data.
- Perform statistical analyses including descriptive statistics, regression modeling, and econometric analyses to support HEOR.
- Develop reproducible analytical workflows using R and statistical programming packages.
- Utilize Excel for data management, validation, exploratory analysis, and analytical reporting, including structured datasets and summary tables.
- Create data visualizations and analytical outputs to communicate insights effectively to research teams and stakeholders.
- Conduct quality checks on data, code, and analytical outputs to ensure accuracy, consistency, and reproducibility.
- Maintain clear documentation of datasets, programming workflows, and analytical processes.
- Collaborate with team to understand research objectives and deliver analytical outputs aligned with research requirements.
Qualifications
- Master’s degree or PhD in Data Science, Statistics, Econometrics, Mathematics, or a related quantitative field.
- Strong expertise in data science, statistical analysis, and applied econometrics.
- Advanced proficiency in R for statistical computing and data analysis.
- Strong proficiency in Excel for data manipulation, validation, and reporting.
- Experience working with healthcare datasets, including EHR or RWE.
- Strong technical documentation and written communication skills.