Job Description
Summary
Interested in driving data science innovation in healthcare? We are seeking a Data Scientist to collaborate on data science projects with utility experts. Will likely work on 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. The Data Scientist is a full-time member of the data science team. As a Data Scientist, you will be responsible for finding creative solutions. The Data Scientist will engage with clinicians, fully understand their research questions and process flows and work collaboratively to address the challenges.
Job Duties
- NLP
- ML
- Development of dashboards, calculations and reports which may require programming in SQL and the like.
- Data management in SQL.
- Development and tuning of machine learning models, which may require programming in Python and/or R
- Preparecomprehensive documented observations, analyses and interpretations of results including technical reports, summaries, protocols and quantitative analyses
- Translatehealthcare challenges into mathematical problems (Requirement and Scope definition)
- Documentthe applications that are developed
- Participate in 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
- Workwith researchers and clinicians to design and implement new NLP components and prepare presentations and publications
- Developinfrastructure for cleaning and processing data and running experiments to evaluate system performance
- Performerror analysis and suggesting and implementing improvements
- Test, debug, and hardencomplex pipelines of NLP components
- Perform other job-related duties as assigned
Minimum Qualifications
- Master’s degree in statistics, science, mathematics or related field.
- Five years of relevant experience.
Preferred Qualifications
- PhD in computer science, math, engineering, stats, or data science.
- Previous experience with VA EMR strongly preferred.
- Should have a proven track record of efficiently conducting and coordinating data analytics projects both independently and collaboratively.
- A background in a diverse field that complements data science (such as applied discipline expertise and statistics) is considered an asset.
- Strong programming skills, interest or experience in NLP research and machine learning, and be passionate about building NLP systems through innovation and experimentation.
- Experience participating in the research process in an academic setting.
- Experience applying machine learning to NLP problems.
Baylor College of Medicine is an Equal Opportunity/Affirmative Action/Equal Access Employer.
Baylor College of Medicine fosters diversity among its students, trainees, faculty and staff as a prerequisite to accomplishing our institutional mission, and setting standards for excellence in training healthcare providers and biomedical scientists, promoting scientific innovation, and providing patient-centered care. - Diversity, respect, and inclusiveness create an environment that is conducive to academic excellence, and strengthens our institution by increasing talent, encouraging creativity, and ensuring a broader perspective. - Diversity helps position Baylor to reduce disparities in health and healthcare access and to better address the needs of the community we serve. - Baylor is committed to recruiting and retaining outstanding students, trainees, faculty and staff from diverse backgrounds by providing a welcoming, supportive learning environment for all members of the Baylor community.