Data Scientist

Position Objective

We are seeking a talented Data Scientist in Digital Health and Behavioral Research to leverage advanced computational and data science expertise in support of innovative research at the National Institute on Drug Abuse (NIDA) within the NIH Intramural Research Program. This role is essential for leading projects that integrate multimodal data, apply machine learning techniques, and enhance our understanding of substance use, treatment outcomes, and recovery.

The ideal candidate will have a robust publication history, showcasing first or senior authorship in peer-reviewed journals, demonstrating significant contributions to the fields of computational modeling, machine learning, AI research, or digital health studies.

Duties and Responsibilities

• Design and execute complex experiments utilizing advanced scientific theories and methodologies.
• Drive scientific innovation by proposing and exploring new, relevant research projects related to human health.
• Develop and apply computational, statistical, and simulation-based designs to test behavioral and digital health research hypotheses.
• Collaborate with research scientists to interpret experimental results and advance research initiatives.
• Independently lead special research projects prioritizing novel treatment developments.
• Assist postdoctoral researchers in statistical analyses for various research projects.
• Evaluate scientific data to establish feasibility for new research programs.
• Offer technical guidance to staff on computational modeling, data analysis, and machine learning methodologies.
• Train laboratory personnel on software and equipment operation.
• Provide expert advice on experimental design, data acquisition, and analysis for publications.
• Participate in collaborative resource allocation discussions within the lab.
• Draft technical reports and manuscripts for academic publication.
• Ensure high data quality and perform analysis on project-related datasets.
• Conduct bioinformatics and statistical data analyses, preparing materials for scientific presentations and manuscripts.
• Maintain comprehensive electronic laboratory notebooks documenting all experimentation.
• Work with research teams to transform research questions into quantitative models and study designs.
• Create and share analytical tools, scripts, and workflows that enhance lab research efficiency.
• Document data pipelines, ensuring reproducibility for all assigned multimodal datasets.
• Curate cleaned and integrated datasets ready for analysis, accompanied by detailed documentation.
• Develop and validate machine learning, NLP, and generative AI models with thorough documentation of methodologies and findings.
• Design computational simulation models with comprehensive documentation of assumptions and analyses.
• Establish version-controlled code repositories that facilitate replication by peers.
• Write technical documents outlining model designs, considerations, and limitations.
• Provide detailed progress summaries on analyses, model performance, and dataset updates.
• Prepare drafts for scientific manuscripts, including methods, results, tables, and figures.
• Create presentation materials for lab meetings and scientific conferences.
• Support human subjects research through the completion of relevant documentation and tracking logs.

Basic Qualifications

• Master's Degree in Computer Science, Information Sciences, Statistics, Social Psychology, or a related field.
• Good Clinical Practice (GCP) certification.
• Experience in Machine Learning, Generative AI, Natural Language Processing, and Computational Simulation Modeling.
• Proficiency in analyzing multimodal time-series data and writing reproducible data science scripts in Python or R.
• Skills in data ordering, presentation, analysis, and standard operating procedure (SOP) writing.
• Familiarity with SQL, Pytorch, TensorFlow, Hugging Face, Pandas, Python, MATLAB, Linux, R, and OpenAI.
• Experience with API integration, AWS, Azure, GitHub, Jupyter Notebook, RedCap, and mobile sensing technologies.

Preferred Qualifications

• Highly organized with excellent multitasking abilities and attention to detail.
• Strong analytical, organizational, and time management skills.
• Exceptional communication skills, both written and verbal.

This job description is intended to outline the core responsibilities and expectations of the position but is not exhaustive. The successful candidate will adapt to the evolving demands of the role as necessary.

GAP Solutions is committed to providing reasonable accommodations for qualified individuals with disabilities, facilitating their ability to perform essential job functions. For accommodation requests, please reach out at recruiting@gapsi.com, referencing the position's requisition number.

Qualified candidates will be considered for employment without regard to race, color, religion, sex, national origin, disability, veteran status, or any other legally protected characteristics.

This position is contingent upon contract award.