Accountabilities:

Conduct exploratory analyses of healthcare populations, clinical conditions, and emerging trends to identify opportunities for reducing healthcare costs and improving patient outcomes.
Analyze large and complex healthcare datasets to identify patterns, assess relationships between variables, and estimate the potential impact of clinical interventions.
Collaborate with clinicians and clinical informaticists to define clinical concepts and extract relevant information from medical, pharmacy, and laboratory claims.
Develop analytical datasets, variables, and features to support statistical modeling, research initiatives, and clinical decision-making.
Apply a broad range of analytical approaches, from descriptive statistics and trend analysis to advanced epidemiological research methods.
Design and conduct clinical outcomes studies and program evaluations using randomized controlled trials, propensity score matching, difference-in-differences models, and other experimental or quasi-experimental methodologies.
Perform literature reviews and intervention research to evaluate engagement rates, treatment effectiveness, and potential outcomes of initiatives in early stages of development or implementation.
Assess clinical intervention opportunities by analyzing treatment effect sizes, population characteristics, and relevant evidence from scientific research.
Write and maintain analytical code using SQL, SAS, and Python to extract, organize, transform, and analyze large healthcare datasets.
Develop statistical models, analytical variables, visualizations, and charts to communicate research findings and support scientific investigations.
Translate complex analytical results into clear insights, practical recommendations, and actionable business opportunities.
Present research findings and strategic recommendations to clinicians, business partners, and other stakeholders, ensuring that results are communicated effectively.
Collaborate with multidisciplinary teams to deliver high-quality analytical projects aligned with departmental and organizational objectives.
Understand broader business strategies, operational priorities, and their connections to clinical innovation and healthcare performance.
Exercise independent judgment when selecting research methodologies, interpreting findings, and addressing complex or ambiguous analytical challenges.
Contribute to the continuous improvement of research methodologies, analytical processes, and evidence-based clinical strategies.

Requirements

Master's degree in a quantitative or research-related discipline, such as Epidemiology, Biostatistics, Economics, Statistics, Clinical Informatics, Engineering, or a related field.
At least 2 years of relevant professional experience in healthcare analytics, research science, epidemiology, biostatistics, data science, or a related discipline.
Demonstrated proficiency in SQL, SAS, and Python, with the ability to create datasets and analytical variables from large and complex data environments.
Experience applying statistical and research methodologies to transform extensive datasets into meaningful, actionable insights.
Practical experience with experimental and quasi-experimental research methods, including randomized controlled trials, propensity score matching, and difference-in-differences modeling.
Strong understanding of statistical analysis, epidemiological principles, hypothesis testing, and research design.
Ability to analyze complex healthcare data, identify meaningful trends, evaluate cause-and-effect relationships, and assess potential clinical and financial outcomes.
Experience collaborating within multidisciplinary teams to deliver rigorous analytical work and communicate findings to business stakeholders.
Excellent written and verbal communication skills, with the ability to explain technical research findings and statistical concepts to both technical and non-technical audiences.
Strong analytical thinking, problem-solving abilities, and attention to detail.
Ability to work independently, exercise sound judgment, and select appropriate research approaches in situations involving ambiguity.

How Jobgether works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

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