Lead Clinical Data Scientist
The Lead Clinical Data Scientist provides advanced statistical and machine learning expertise to the Clinical Data Science team and plays a critical role as a leader of internal and client-facing research efforts. This role will contribute to development, communication, and execution of statistical analysis plans, including machine learning modeling approaches, in support of digital biomarker and predictive model research on the AiCure platform. The applicant will interface with clients to understand client objectives and present analysis plans and results, as well as collaborate with the broader AiCure team to support predictive model development, validation, and deployment. They will be responsible for the execution of data science activities aligned to digital biomarker and patient behavior predictive modeling including exploratory data analysis, statistical analysis, inference model development, data visualizations, and data quality assessment. Salary range: $90,000 to $150,000.
- Perform exploratory data analysis and statistical testing for measurement and validation of novel disease and behavioral digital biomarkers.
- Develop inference/predictive models of patient behavior with machine learning and statistical methods utilizing complex, high dimensional digital biomarker and other available data.
- Review client study protocols in collaboration with Clinical Data Science staff to propose relevant analyses of audio and visual digital biomarkers that align with study objectives.
- Develop statistical analysis plans for client studies utilizing cross-sectional and longitudinal digital biomarker measurements and standard clinical assessments.
- Interface across AiCure departments to provide study configuration, data collection, and statistical analyses in support of ongoing client studies.
- Independently execute experimental plans, interpret and communicate results to department leadership.
- Develop data visualizations for complex, high dimensional digital biomarker data, model performance, and other product offerings as needed.
- Interface closely with engineering and product teams to translate novel digital biomarkers and inference models into engineered product applications.
- Mentor junior staff and student interns.
- Present and interpret results to a wide array of clinical, technical and lay audiences.
- Participate in manuscript writing for results publication, authors abstracts, and presents at professional conferences.
Required Education & Training
- Bachelor’s degree in relevant field required
- Master’s degree, PhD, or equivalent in in data science, machine learning, statistics, mathematics, or a related field.
- Demonstrated knowledge and experience with statistical analysis methods including hypothesis testing, linear and non-linear regression, repeated measures analysis.
- Mastery of one or more statistical analysis platforms such as R, Python statsmodels, SAS.
- 3+ years of programming experience in either applied educational or professional projects with commonly used language such as Python, Java, C++.
- 3+ years of experience in either applied educational or professional projects with widely used statistical analysis and machine learning libraries such as ScikitLearn, Weka, R.
- 1+ years of experience in either applied educational or professional projects with widely used deep learning libraries such as PyTorch, TensorFlow.
- 3+ years of experience with progressively more complex data science, applied statistics, or machine learning projects.
- Familiarity with SQL.
- Familiarity with cloud computing environment such as Amazon Web Services (AWS) or Google Cloud Platform (GCP).
- Strong verbal and written communications skills with the demonstrated ability to explain complex technical concepts to a lay audience.
- Demonstrated educational or professional scientific and technical writing experience.