The Senior Data Scientist provides programming, advanced statistical, and machine learning expertise to the Clinical Data Science team in support of digital biomarker and predictive model research on the AiCure platform and will work closely with the broader AiCure team to execute analyses in accordance with customer requirements. 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.
- Develop high-quality code implementing validated digital biomarker analysis and inference models as application programming interfaces
- Perform exploratory data analysis, statistical testing, and inference model development for measurement and validation of novel disease and behavioral digital biomarkers.
- Develop predictive models of patient behavior with machine learning and statistical methods utilizing complex, high dimensional digital biomarker and other available data
- Contribute to assessment and implementation of computational, algorithmic, and predictive analytics approaches to address assigned research questions
- Make substantial contributions to the experimental design and scope of research projects including data requirements, method selection, analysis and validation approaches
- 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
- Develop data quality metrics, develop and execute data quality assessments
- Interface closely with applications research to translate novel digital biomarkers and inference models into engineered product applications
- Contribute to the design and conduct of continuous validation plans for production systems that incorporate digital biomarkers and predictive models
- Mentor junior staff and student interns
- Present and interpret results to a wide array of clinical, technical and lay audiences
- Managing and delivering a portfolio of client deliverables, including client-facing written and verbal communications across multiple projects
- Participate in manuscript writing for results publication, authors abstracts, and presents at professional conferences
- Master’s degree in computer science, data science, machine learning, statistics, mathematics, informatics or a related field
- 3+ years of experience with progressively more complex data science, applied statistics, or machine learning projects
- Demonstrated experience in building Python libraries and programming in Python for model development in either applied educational or professional projects
- Demonstrated experience with cloud computing environment such as Amazon Web Services (AWS) or Google Cloud Platform (GCP)
- Demonstrated experience with machine learning model development and validation. Ability to independently train and evaluate machine learning models using standard algorithms such as random forest, logistic regression, and support vector machines
- Demonstrated experience in either applied educational or professional projects with widely used statistical analysis and machine learning libraries such as ScikitLearn, R
- Knowledge and experience with statistical analysis methods
- Demonstrated experience in ETL processes using SQL queries to pull and transform data
- 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
- Passion for science, research, and building innovative technologies in a collaborative, team-oriented environment
Demonstrated experience in either applied educational or professional projects with widely used deep learning libraries such as PyTorch, TensorFlow
What We Do
Everyone responds differently to disease and treatment. We are working to understand how.