Sr. Data Scientist - Research & Analytics

Job Description Job Description About Syapse Syapse is a real-world evidence company on a mission to improve outcomes for all patients facing serious disease. By integrating complete, longitudinal, and continuously updated real-world patient data, we can provide unique insights into patients’ care journeys. Our advantage derives from a decade of partnership with the world’s largest Learning Health Network of innovation-driven healthcare systems. Syapse enables providers to operationalize precision medicine and deliver the best care today to their patients while helping life sciences companies and regulators accelerate the development and approval of new therapies for patients tomorrow. Together we are working toward a future in which all patients have access to the best precision care. About the role As a Sr. Data Scientist, you will be responsible for driving projects that require diving deep into clinical data, completing analyses, and developing pipelines, tools, and R packages. You will collaborate with fellow data scientists, work in close partnership with epidemiologists, and coordinate with other teams including product, engineering, informatics, alliance management, and clinical KOLs. You will need to execute against multiple deliverables simultaneously in a fast-paced and mission-driven environment. You’ll enjoy solving the riddles associated with extracting, manipulating, and structuring data from complicated healthcare concepts into digestible, statistically rigorous insights. As a Research and Analytics Senior Data Scientist, you will develop best practices, work with the data science team to find patterns in cancer care, and help curate the narrative of the data. What You’ll Accomplish Clean, orient, and derive data elements from real-world healthcare data through data wrangling, pipeline engineering, algorithmic tooling, and analytical insight for use in research and the Analytical Datasets. Support the development of data products & other product offerings. Serve as a Data Scientist lead on retrospective studies. Develop algorithms to interpret real-world data and derive insights. How You’ll Spend Your Days You’ll work with real-world data (RWD) and tackle novel RWD challenges. You’ll work side-by-side with researchers at Life Sciences companies, the FDA, and health systems to impact U.S. cancer care and its evaluation. You’ll develop R packages and pipelines to codify best practices for interpreting RWD across many domains (biomarker testing, procedures, medications, etc.). What You Bring to the Table Education & Experience Minimum Requirements Degree in one of the following fields: Computer Science, Data Science, Statistics, Biostatistics, Epidemiology, Mathematics, Informatics, Genetics, or related. Bachelor’s Degree +7 years or Advanced Degree +4 years professional experience explicitly working with applied data in oncology and/or precision medicine, including structuring data and performing analysis. Hard Skills Content knowledge. You have years of professional experience building data products and/or models with multisource healthcare Real World Data. Programming experience. You’ve built R packages and know your way around Tidyverse & Shiny. Demonstrated experience with relational databases, particularly SQL. Knowledge of statistical theory including generating descriptive statistics, data visualization, hypothesis testing, and regression modeling. Teammate Skills Communication. You say what you mean and be able to break down complex ideas for a non-technical audience. Curiosity. You are someone who finds the answers to interesting questions. You ask questions when unsure and to more deeply understand concepts. Collaboration. You thrive in a collaborative atmosphere and are able to translate input and expertise from multiple sources into your own expert, independent deep-work. You are open to giving and receiving feedback freely and kindly. Bonus Points Demonstrated R package or shiny app development experience. Knowledge of survival analysis. Established publication history. Compensation The target base salary for this position is $150,000-$175,000. This base salary is only a part of a total compensation package that includes: an annual performance bonus based on personal and company performance, robust benefits, 401k with match, and flexible PTO. Individual pay may vary from the target range as a number of factors including market forces, experience, location, disparities in market data and other relevant business considerations may all factor into final compensation. #J-18808-Ljbffr