G

Guidehouse

Advises agencies and runs regulated operations

Databricks Data Scientist

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeRemote in USA$113k - $188k /yr

About the Job

Requirements

  • A bachelor's degree in computer science, engineering, mathematics, statistics, or another relevant field is required.
  • Three to eight years of relevant experience in data science, machine learning, or advanced analytics is required.
  • Strong experience with Python and SQL for data analysis, modeling, and transformation is required.
  • Experience with Databricks, Spark, Delta Lake, or similar cloud-native data platforms is required.
  • Hands-on experience designing, building, evaluating, and deploying machine learning models, including moving models from prototype to production or production-like environments, is required.
  • Experience with machine learning lifecycle practices, including experiment tracking, model evaluation, model registry, version control, deployment workflows, monitoring, and retraining approaches, is required.
  • Familiarity with model serving patterns, API-based inference, scheduled batch scoring, and integrating model outputs into dashboards, applications, or operational workflows is required.
  • Experience with data preparation, feature engineering, and model development is required.
  • Ability to analyze data and communicate insights clearly is required.
  • Ability to troubleshoot technical issues, communicate recommendations clearly, and work effectively in team-based delivery environments is required.
  • Experience supporting AI governance practices, including model documentation, validation, monitoring, version control, and responsible AI considerations, is required.
  • Ability to work across data science, data engineering, cloud, security, and client stakeholder teams to translate analytical prototypes into scalable, maintainable solutions is required.

Responsibilities

  • 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 practices.
  • Monitor deployed models for performance, drift, data quality, usage patterns, and operational issues; recommend retraining, tuning, or retirement actions as needed.
  • Analyze data to identify trends, patterns, and insights to support business decisions.
  • Translate business requirements into analytical approaches, models, and data science solutions.
  • Perform data validation, quality checks, and issue resolution to ensure accuracy and consistency.
  • Collaborate with cross-functional teams, including data engineers, analysts, and business stakeholders.
  • Communicate model outputs, analytical findings, and recommendations to technical and non-technical audiences.
  • Document models, datasets, and methodologies to support reproducibility, transparency, and reuse.
  • Follow data governance, security, and compliance standards within the platform.

Desired Qualifications

  • Two or more years of hands-on experience with the Databricks platform.
  • An active Databricks Machine Learning Engineer, GenAI Engineer, Data Analyst, or related certification.
  • Experience with Databricks MLflow, Feature Engineering, Feature Store, Model Serving, Workflows, Unity Catalog, Mosaic AI, Vector Search, AI Gateway, or related Databricks AI/ML capabilities.
  • Experience developing GenAI, LLM, RAG, agentic AI, or prompt evaluation workflows using Databricks Mosaic AI, MLflow, open-source frameworks, or cloud-native AI services.
  • Experience with CI/CD, automated testing, code packaging, environment promotion, and source control practices for data science and machine learning workloads.
  • Experience with machine learning frameworks and statistical modeling techniques.
  • Experience with cloud platforms such as Azure, AWS, or GCP.
  • Experience working in project-based or consulting delivery environments.
  • Familiarity with data modeling, data warehousing, and large-scale data processing concepts.

About the Company

Guidehouse

Advises agencies and runs regulated operations

Guidehouse advises government agencies and companies in regulated industries on strategy, technology and day-to-day operations. Its work combines business advice with software implementation and ongoing management, so a client uses the same firm to plan a change, build the systems and run the resulting processes. Teams modernize cloud platforms, apply data analysis and artificial intelligence, and redesign organizations to meet operating and regulatory requirements. Clients pay for consulting projects and technology work or outsource continuing business functions to its managed services teams. Guidehouse was founded in 2018 and is headquartered in McLean, Virginia.

Company size
10,001+
Company stage
Acquired
Total funding
$750K
Headquarters
McLean, VA
Founded
2018

Recently Posted Jobs

Explore more opportunities at Guidehouse

See more jobs