Data Scientist

Position Objective

We are seeking a skilled Data Scientist specializing in Digital Health and Behavioral Science to bring advanced computational and data science expertise to transformative research projects within the NIH Intramural Research Program, particularly within the National Institute on Drug Abuse (NIDA). This role focuses on multimodal data integration, machine learning, and simulation modeling to better understand substance use, treatment outcomes, and recovery. The ideal candidate will have a robust publication record, showcasing first-author, senior-author, or significant middle-author contributions to research in computational modeling, machine learning, AI-driven studies, or digital health.

Duties and Responsibilities

• Design and conduct innovative experiments requiring a comprehensive understanding of scientific theories and principles.
• Propose and initiate new research projects that have the potential to advance the field of human health significantly.
• Develop and implement statistical and simulation-based experimental designs for testing digital health hypotheses.
• Collaborate with staff to analyze and interpret experiments conducted by research scientists.
• Independently manage high-priority research projects, particularly the development of novel research treatments.
• Provide statistical analysis support alongside postdoctoral researchers and biological scientists.
• Evaluate scientific data to ascertain the feasibility of developing a research program around new ideas or data.
• Offer technical guidance on computational modeling, machine learning techniques, and data analysis strategies.
• Operate, troubleshoot, and train others on laboratory equipment and software.
• Assist users in designing experiments, utilizing instrumentation, conducting data acquisition, and preparing figures for publication.
• Participate in laboratory planning and review future proposals for resource allocation.
• Write technical reports and prepare manuscripts for publication to disseminate research findings.
• Oversee data quality for research projects and conduct thorough data analysis and interpretation.
• Carry out bioinformatics analyses and prepare data for abstracts and manuscripts.
• Maintain a comprehensive electronic laboratory notebook detailing all experimental procedures and outcomes.
• Collaborate with investigators to translate research inquiries into quantitative models and evidence-based study designs.
• Develop and share analytical tools, scripts, and reproducible workflows to enhance laboratory research.
• Ensure fully documented data pipelines, providing reproducible processes for multimodal datasets.
• Compile analysis-ready datasets, complete with data dictionaries and thorough processing documentation.
• Implement and validate machine learning, NLP, and generative AI models, ensuring rigorous documentation of methodologies and results.
• Construct computational simulation models, detailing assumptions and calibration processes.
• Maintain version-controlled code repositories with comprehensive documentation to facilitate replication by other researchers.
• Provide comprehensive model documentation covering design decisions, input features, and modeling limitations.
• Draft written summaries outlining completed analyses, model performance, and future steps.
• Prepare and revise scientific manuscripts, including methods, results, tables, and figures suitable for peer-reviewed journals.
• Create presentations and materials for internal reviews, lab meetings, and scientific conferences.
• Support human subjects research by documenting consent processes and participant tracking.

Qualifications

Basic Qualifications:

• Master's Degree in Computer Science, Information Sciences, Statistics, Decision Science, Social Psychology, or a related discipline.
• Familiarity with Good Clinical Practice (GCP) standards.
• Experience in Machine Learning, Generative AI, Natural Language Processing (NLP), and Computational Simulation Modeling.
• Proven expertise in analyzing Multimodal Time-Series Data, and crafting reproducible data science in Python/R for human subjects research.
• Experience in managing supplies, data presentation, data analysis, and writing standard operating procedures (SOPs).
• Proficiency in SQL, Pytorch, TensorFlow, Hugging Face, Pandas, Python, MATLAB, Linux, R, and Open AI.
• Experience with API Integration, cloud services (AWS, Azure), GitHub, Jupyter Notebook, RedCap, and Mobile Sensing Platforms.

Preferred Qualifications:

• Strong ability to manage multiple tasks while maintaining attention to detail.
• Excellent analytical, organizational, and time management capabilities.
• Exceptional communication skills, both written and verbal.

This job description does not encompass all activities, duties, or responsibilities required for this role. Success in this position requires performing each essential duty satisfactorily. The requirements listed are representative of knowledge, skills, and abilities needed. Reasonable accommodations may be provided for qualified individuals with disabilities. GAP Solutions is committed to providing reasonable accommodations to qualified individuals with disabilities. If you need accommodation to apply for this position, please reach out via email. Include the requisition number of your desired position. Note that this email is only for accommodation requests; other inquiries will not receive a response. Qualified applicants will be given consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, or any other characteristic protected by law. This position is contingent upon contract award.