We are hiring a Senior Data Analyst to work with large data on research to improve care for substance use disorder treatment services for New Yorkers.
The analyst will collaborate with interdisciplinary teams in a world-class research institution to address questions of health and health equity.
Using advanced statistical techniques and programming skills, the Senior Data Analyst will conduct analyses with large datasets including Medicaid claims data, administrative data sets and other data sources.
The Senior Data Analyst will work alongside multiple faculty members and external partners and independently lead, develop and complete analyses of large datasets for descriptive and inferential studies.
These studies can include estimation of program effects, describing characteristics of populations and their healthcare, and tracking trends in mortality and morbidity, and service utilization.
The role responsibilities include making decisions and recommendations about techniques, scope, and approaches appropriate to the research project.
Minimum Qualifications :
To qualify you must have a Masters degree in a quantitative discipline (Biomedical or Clinical Informatics, Epidemiology, Biostatistics, Computer Science, Machine Learning, Applied Statistics, Mathematics or similar field) and 3 years of experience in data science.
- Outstanding verbal and written communication skills;
- Strong time-management and prioritization skills; ability to work well under pressure and in a team;
- Experience working with key secondary data sources;
- Skilled in large-scale data wrangling;
- Proficiency in at least one programming language (Python, R, Stata, SQL) and visualization tools ( Tableau)
Preferred Qualifications :
Programming proficiency in Python, R, and SQL with additional experience in SAS. Experience building and maintaining packages in Python is a plus.
Experience managing large datasets.
Experience using version control software, including Github.
Knowledge of causal inference methodologies and experience working with longitudinal, clustered data.
Past experience working with health care data. This includes insurance claims data, administrative data, electronic health record data, or other registry databases.
Relatedly, knowledge of commonly used coding systems (, ICD-10, CPT, HCPCS, NDC).
Experience supervising data analysts.
Qualified candidates must be able to effectively communicate with all levels of the organization.