Data Scientist: Reproducible Analytics for NIH (On-Site)

Guidehouse; Bethesda (MD); On-site; USD 65,000 - 108,000; Full time

Benefits offered by this job

Medical Insurance

401(k)

Parental Leave

Paid Holidays

Job summary

Guidehouse seeks a Data Scientist for a full-time, on-site role supporting NIH research initiatives in Bethesda, MD (onsite) or Baltimore, MD. You’ll turn complex real-world data into analytics and decision-support products with reproducible workflows and careful handling of sensitive information.

You’ll build pipelines, perform descriptive and predictive analyses, develop models, and deliver dashboards to researchers and program managers while staying current with emerging methods and tools.

Qualifications

• Bachelor's degree required and at least 1 year in data science or research support.
• Experience with Python and/or R for data processing, analysis and visualization.
• Familiarity with NLP, Generative AI, LLMs, and time series analysis.
• Ability to write SOPs and document technical work.

Responsibilities

• Collect, clean, integrate, and validate data from diverse sources.
• Develop reproducible analytical pipelines and statistical models.
• Create dashboards and visualizations for technical and nontechnical stakeholders.
• Collaborate with researchers, data engineers, and IT professionals.

Skills

Python

R

NLP

Generative AI

LLMs

Time series analysis

Data analysis

Documentation

Education

Bachelor's degree

Tools

AWS

Azure

PyTorch

TensorFlow

Hugging Face

OpenAI

Python ecosystems

Job description

Guidehouse seeks a Data Scientist for a full-time, on-site role supporting NIH research initiatives in Bethesda, MD (onsite) or Baltimore, MD. You’ll turn complex real-world data into analytics and decision-support products with reproducible workflows and careful handling of sensitive information.

You’ll build pipelines, perform descriptive and predictive analyses, develop models, and deliver dashboards to researchers and program managers while staying current with emerging methods and tools.