Data Scientist

Leidos•Houston, TX

About The Position

Belong. Connect. Grow. The Human Health and Performance Contract 2 (HHPC2) are a team of innovators, thinkers, creators, explorers, volunteers and dreamers and we all share one goal: to improve the world responsibly and safely. On HHPC2 we are at the forefront of safeguarding astronaut health, ensuring human performance, and advancing technologies for human space exploration. We are seeking a Data Scientist with a strong life science to support the Human Research Program's at the Johnson Space Center (JSC). What You’ll Do: You will be a member of the Life Sciences Data Archive (LSDA) project within the Exploration Medicine Integration Office (EMIO). In the Data Coordinator role, you will work across multiple teams and systems to identify, extract, and process data to support information exploitation. This will require working with a variety of domain specialists to understand the information needs, and an ability to provide a solution in a timely manner. Often, the response is organized and well-structured data. Other times, the response may be a review and summarization of the data, or a qualitative breakdown. The requirements vary broadly, depending on the stakeholder role and expected outcomes. In order to maximize the value and reuse of data, the federal government and NASA have a mandate to create datasets that adhere to the FAIR principles (Findable, Accessible, Interoperable, and Reusable). Part of the responsibility of the Data Coordinator will be to ensure information within the LSDA aligns with the FAIR principles, which requires an awareness of what makes data FAIR and how to transform datasets to be FAIR compliant. What You Bring: The LSDA team is tasked with the curation of data from human or human-related studies funded by NASA’s HRP. Therefore, experience in both the biological and data science disciplines is essential to performing the functions of this position. You will rely on your experience and judgment to plan and accomplish the goal of transforming high-value data residing in or submitted to our repository to formats that enable data-driven decision making for exploration missions. This position requires you to extract complex data from a variety of file types and formats to generate organized and reuseable data products. Additionally, you are expected to contribute to the ongoing development of NASA’s Life Sciences Portal (https://nlsp.nasa.gov) which houses the data produced from HRP-funded studies and supports the team’s data management workflows. These contributions involve developing system requirements and participating in user acceptance testing activities.

Requirements

Bachelor’s degree in biological, bioinformatics, computational biology or related field with less than 2 years of relevant experience.
Demonstrated experience in data wrangling including extracting and transforming different types of data files (csv, xlsx, pdf, doc, DICOM, etc.) into analyzable data using reproducible coding and scripting techniques.
The ability to obtain and maintain a Public Trust clearance.
Experience working with human data
Experience with common data manipulation software such as shell tools, R or Python
Understand database design and create processes for extracting and auditing data
Experience manipulating large datasets and working with raw, untidy data
Experience with data wrangling and harmonization across a variety of data file types and formats
Familiarity with enterprise vocabulary standards and how to use them for data integration and harmonization
Experience developing data visualizations
Proficiency with Microsoft Office Suite products
Effective planning, problem solving, and decision-making skills
Ability to work effectively both in small teams and independently
Ability to work effectively in a multidisciplinary setting
Ability to excel in fast-paced environments and set priorities appropriately
Highly developed organizational skills and attention to details
Excellent oral and written communication skills. Ability to communicate effectively with project managers, project leaders, principal investigators, customers, and colleagues is essential.

Nice To Haves

Master’s degree in Data Science
Knowledge of FAIR (findable, accessible, interoperable, reusable) principles
Experience working with relational databases or digital repositories
Experience with data formatting, cataloging, and storage
Experience extracting, manipulating, and analyzing data in cloud-based environments
Experience with data extraction and manipulation using AWS tools
Knowledge of regulatory and legislative requirements related to PII and data privacy laws
Proficient in using SQL to find, combine, and extract data from relational databases
Comfortable utilizing Unix or Windows shell tools and operating within a terminal interface

Responsibilities

Integrate information from multiple data sources, solving common transformation problems, and resolving data cleansing and quality issues
Verify quality control and quality assurance of data during data extraction and manipulation
Maintain data dictionaries to document relational databases and extracted data
Work closely with archivists and database administrators to identify data issues and solutions
Develop scripts and workflows to create analyzable datasets, tables, listings, and figures; create reports, visualizations, and interactive dashboards
Proficiency working within Unix/Linux shell environments; ability to navigate, query, and manipulate files using command-line tools (e.g., bash, awk, sed) and scripting languages such as Python.
Experience transforming, normalizing, and restructuring heterogeneous or poorly formatted data into clean, structured datasets suitable for analysis.
Demonstrated ability to aggregate, summarize, and evaluate datasets through reproducible data workflows and scripting.
Skilled in parsing, validating, and converting data across formats (e.g., CSV, JSON, XML) and implementing data quality checks.
Ability to design efficient data pipelines for ingestion, cleaning, transformation, and documentation of complex datasets.
Familiarity with version control, metadata standards, and reproducible research practices to ensure traceable and auditable data management.
Understand, create, and modify SQL queries as needed to find, combine, and extract data from existing relational databases
Ability to identify and appropriately handle Human Subjects Research data, implement required security, access controls, and data protection measures in compliance with NASA and broader federal regulatory standards
Maintain current CITI Human Subjects Research - Biomedical Research certification
Maintain confidentiality of all medical and personal information to which access has been granted
Provide weekly status reports of work activities to team leader
Other duties as assigned