Databricks Data Scientist

Role Overview

Guidehouse is seeking a Databricks Data Scientist to join its AI & Data team and support client projects in advanced analytics, machine learning, and data science solutions. The role focuses on developing models, generating insights, and enabling data-driven decision-making in collaboration with clients and stakeholders.

What You Will Do

• Develop and evaluate machine learning and statistical models to support business and mission needs.
• Prepare 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.
• Build reusable feature engineering workflows and model training pipelines using Databricks notebooks/workflows and MLflow.
• Manage the ML lifecycle with MLflow Model Registry and Unity Catalog-based governance (register, version, promote, document).
• Monitor deployed models for performance, drift, data quality, usage, and operational issues; recommend retraining/tuning/retirement.
• Conduct data analysis to identify trends, patterns, and actionable insights.
• Translate business requirements into analytical approaches, models, and data science solutions.
• Perform data validation and quality checks; resolve issues affecting accuracy/consistency.
• Collaborate with data engineers, analysts, and business stakeholders.
• Communicate results to technical and non-technical audiences.
• Document models, datasets, and methodologies to ensure reproducibility and reuse.
• Follow data governance, security, and compliance standards within the platform.

What You Will Need

• Bachelor’s degree in CS, engineering, mathematics, statistics, or related field.
• 3–8 years of relevant experience in data science, machine learning, or advanced analytics.
• Strong Python and SQL skills for analysis, modeling, and transformation.
• Hands-on experience with Databricks and Spark/Delta Lake (or similar cloud-native platforms).
• Experience designing, building, evaluating, and deploying ML models (moving from prototype to production or production-like environments).
• Experience with ML lifecycle practices: experiment tracking, model evaluation, registry/versioning, deployment workflows, monitoring, retraining.
• Familiarity with model serving patterns such as API-based inference and scheduled batch scoring, and integrating outputs into dashboards/apps/ops workflows.
• Ability to analyze data and communicate insights and recommendations clearly; troubleshoot issues in team delivery environments.

Remote / Location Notes

• Virtual work flexibility within the United States; remote candidates considered.
• Preference for candidates located near Guidehouse offices in: Arlington, VA; Washington, DC; New York, NY; Chicago, IL; Austin, TX; Atlanta, GA; Boston, MA; Boulder, CO.
• This requisition supports multiple hiring levels for Databricks Data Science teams.