The primary function of this position is to utilize data science skills in data wrangling/munging to extract and transform data to produce analyzable datasets for the purpose of reproducible access, display, and analysis in support of ongoing investigations in NASA’s biomedical research laboratories.
As a member of this team, the incumbent must possess the ability to use programming and scripting to extract data from multiple file types and formats to generate useable data, create automated reports, and build interactive dashboard visualizations. Responsibilities include the development of scripts to automate data extraction and formatting, and the generation of reports and visualizations. Scripts may be coded using a variety of statistical software, such as R, Python, and MATLAB, depending on investigator needs.
- Responsible for compliance with Safety, Health and Environmental plan; must be committed to a high standard of safety and be willing and able to comply with all safety laws and all of the Company’s safety policies and rules and must be willing to report safety violations and potential safety violations to appropriate supervisory or management personnel.
- Responsible for compliance with the Quality Assurance Plan, policies and procedures.
- Must maintain regular and acceptable attendance level as determined by the Company.
- Responsible for completing all assigned training.
- Programming to perform data transformations, including merging, ordering, aggregation, etc., using vetted data science software (e.g. R, Python, or MATLAB) to develop automated computational pipelines for complex data.
- Processing, cleansing, and verifying the integrity of data used for analysis.
- Integrate information from multiple data sources, solving common transformation problems, and resolve data cleansing and quality issues.
- Develop automated reports and visualizations tools, such as interactive dashboards.
- Know the context for the data well enough to be able to accurately assemble, clean, and transform it into a meaningful form useful for subsequent analysis.
- Implement statistical or other mathematical methodologies as needed for specific models or analysis as directed.
- Effectively communicate with managers and researchers across different disciplines regarding data sets and reporting needs.
- Understand and collaborate with scientists and management to devise solutions to meet reporting requirements.
- Maintain current CITI Human Subjects Research - Biomedical Research certification.
- Other tasks as directed.
- Bachelor’s degree or certification in Data Science, Computer Science, Mathematics, Statistics, or similar quantitative field or at least 4 years relevant experience working with data
- Demonstrated experience in Data Science including extracting and transforming different types of data files (csv, xls, txt, pdf, doc) into useable data using reproducible coding and scripting techniques.
- Minimum 4 years of programming code in software packages such as R, Python, MATLAB, etc. to perform data manipulation
- Demonstrated experience in developing informative visualizations.
- Established competency with data science techniques for data wrangling/munging.
- Host GitHub repository with example projects.
- Data-oriented personality. Superior analytical, planning, problem solving, and decision-making skills.
- Good scripting programming skills.
- Experience with common data science toolkits, such as R or MATLAB. Excellence in at least one is highly desirable.
- Ability to learn and implement new techniques and skills, and seek guidance when needed.
- Excellent written and oral communication skills including effectively explaining concepts to managers and scientists.
- Ability to work effectively in a multi-disciplinary setting.
- Ability to effectively manage multiple concurrent tasks and seek direction on competing priorities.
- Experience with data visualization tools, such as plot.
- Experience developing data visualizations and interactive dashboards through coding.
- Experience with data wrangling and harmonization across a variety of data file types and formats.
- Experience working with and creating data architectures.
- Demonstrated experience with collaborations supporting multiple research disciplines/specialties.
- Ability to be creative in developing different methods for reporting and communicating data insights depending on the specific needs of a project.