Senior Biostatistics and Data Science Associate
The Center for Innovations in Quality, Effectiveness and Safety (IQuESt) is looking for data scientists to collaborate on data science projects with utility experts. We work on cool projects like health risk assessment, predicting adverse outcomes, signal processing and natural language processing (NLP). The ideal candidate will have significant experience using Python, and R, R Shiny, and MATLAB in multiple analytical applications, such as nonlinear time series analysis, machine learning (for example, binomial/regression models or ensemble models), deep learning (for example, NN, CNN, and RNN), and probability, statistics, and NLP. As with any successful analytics project, it all starts with the data, so you should have experience extracting and transforming data from relational databases, i.e. SQL Server. We work with population-level data, so experience with exceptionally large data sets is a plus. This individual will be a full-time member of our data science team. They will be responsible for finding creative solutions to challenges faced by clinical investigators through an evidence-based approach. These solutions will be found by introducing machine learning and other data science concepts and building applications within a scripting language, such as Python, R, etc. This individual will engage with clinical collaborators to fully understand their clinical questions and process flows to make sure the solution that is provided to them will address the challenges successfully.
The ideal candidate has an MS, or PhD in computer science, math, engineering, stats, or data science. They should have a proven track record of efficiently conducting and coordinating data analytics projects both independently and collaboratively over at least a two-year period for junior positions or a five-year period for senior positions. Exceptional educational or industry experience can offset any particular requirement. A background in a diverse field that complements data science (such as applied discipline expertise and statistics) is considered an asset.
- Translate healthcare challenges into mathematical problems (Requirement and Scope definition).
- Develop dashboards, calculations, and reports which may require programming in SQL or alternate programming language.
- Utilize classification modeling and decision tree models with random forest and the accompanying boosting algorithms.
- Perform Anomaly detection modeling with isolated forests, PCA, and K-Means clustering.
- Utilize recommendation systems and time series prediction models.
- Use model selection, evaluation, and interpretation concepts like regularization, dimension reduction, and cross-validation.
- Develop and tune machine learning models, which may require programming in Python and/or R.
- Prepare comprehensive documented observations, analyses and interpretations of results including technical reports, summaries, protocols and quantitative analyses.
- Attend regular progress meetings with clinical collaborators (multiple times a week) face to face or via on-line meeting software. This may include working on-site. Pending COVID-19 travel and working restrictions.
- Bachelor's degree.
- Four years of relevant experience.
Baylor College of Medicine is an Equal Opportunity/Affirmative Action/Equal Access Employer.
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