Guidehouse

Databricks Data Scientist

Washington, DC, US$113,000-$188,000Posted 25 days ago

Job Description

Job Family

:

Data Science & Analysis, Data Science Consulting Travel Required:

None Clearance Required:

None Guidehouse is seeking a Databricks Data Scientist to join our AI & Data team to support client projects involving advanced analytics, machine learning, and data science solutions. This role focuses on working with data to develop models, generate insights, and support data-driven decision-making across teams. The role requires strong Python and SQL skills, analytical thinking, and the ability to collaborate with clients and stakeholders to deliver scalable data science solutions.

This position offers virtual work flexibility within the United States. While remote candidates will be considered, preference will be given to candidates located near a Guidehouse office in one of the following markets: Arlington, VA; Washington, DC; New York, NY; Chicago, IL; Austin, TX; Atlanta, GA; Boston, MA; and Boulder, CO.

Please note, this requisition supports hiring across multiple levels to support our Databricks Data Science Teams. The posted salary range represents a range of potential compensation and will vary based on the selected candidate’s experience, qualifications, location, and the level at which the position is filled.

What You Will Do

  • Develop, train, and evaluate machine learning and statistical models to support business and mission needs using the Databricks platform.
  • Prepare, clean, and maintain datasets for modeling, experimentation, and analysis.
  • Write, optimize, and maintain Python and SQL workflows for data exploration, feature engineering, and model development.
  • Work with large-scale datasets using Databricks, Spark, and Delta Lake platforms.
  • Design reusable feature engineering workflows and model training pipelines using Databricks notebooks, workflows, and MLflow.
  • Register, version, promote, and document models using MLflow Model Registry and Unity Catalog-based model governance

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