Quantitative Scientist, Osmind

• PhD or Master’s degree in a quantitative discipline such as applied statistics, mathematics, biostatistics, data science, epidemiology, health economics outcomes research, or a related discipline
• 3+ years full-time work experience conducting quantitative research in industry or consulting settings
• Experience writing analysis protocols and conducting statistical analyses on clinical data collected from human subjects, such as electronic health records, claims databases, observational studies, or clinical trials, with related methodological expertise in statistical analysis of observational data
• Experience communicating results in reports and preparing formal scientific communications such as manuscripts, abstract, and presentations
• Strong data intuition and data communication skills. Ability to communicate findings to both internal and external stakeholders and quickly align on next steps
• 3+ years using open-source programming languages (Python or R) for data cleaning, statistical analyses, data visualization, and generating reports
• Proficient in using SQL to clean data and build analysis datasets
• Experience consolidating and cleaning data from disparate sources
• Applied experience in core machine learning principles, such as cross-validation, feature selection, hyperparameter tuning, and model selection
• Experience using Git/Github and knowledge of version-control best practices

Desirable

• Join our cross-functional Biosciences team, where you’ll collaborate closely with our data and research teams to plan and deliver on research projects with Osmind real-world data
• Contribute to real-world evidence with both life sciences partners and academic research partners. Advance the development of breakthrough mental health treatments for the patients who need it most
• Support high-priority initiatives by building new research cohorts and iterating in collaboration with clients and internal stakeholders
• Support life sciences business development by conducting exploratory analyses of real-world data and evaluating data quality to assess feasibility of proposed research initiatives
• Conduct cutting-edge research that directly impacts our field:
• Prepare statistical analysis plans and execute analyses on treatment outcomes, treatment utilization patterns, comparative effectiveness research, patient subtyping, treatment response prediction, etc
• Provide subject matter expertise on the tradeoffs of various statistical approaches and create analysis roadmaps to meet specific project objectives
• Prepare abstracts, posters, oral communications, manuscripts, etc. for presentation at scientific conferences and peer-reviewed publications
• Contribute to data pipelines for clinical research datasets to support Osmind’s life sciences and internal scientific research
• Grow our real-world data products by highlighting opportunities for improvement in depth of data capture and structure of research datasets
• A successful first year might look like
• Contribute to Biosciences research projects leading to novel scientific findings presented at conferences and/or publications
• Assist life sciences business development by building new research cohorts and assessing feasibility of new projects
• Design approaches and deliver impactful results on high-priority life sciences projects, ultimately impacting patients