Databricks Data Scientist

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 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 both 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.

What You Will Need:

Bachelor’s degree in computer science, engineering, mathematics, statistics, or another relevant field.

3-8 years of relevant experience in data science, machine learning, or advanced analytics.

Strong experience with Python and SQL for data analysis, modeling, and transformation.

Experience with Databricks, Spark, Delta Lake, or similar cloud-native data platforms.

Hands-on experience designing, building, evaluating, and deploying machine learning models, including experience moving models from prototype to production or production-like environments.

Experience with ML lifecycle practices including experiment tracking, model evaluation, model registry, version control, deployment workflows, monitoring, and retraining approaches.

Familiarity with model serving patterns, API-based inference, scheduled batch scoring, and integration of model outputs into dashboards, applications, or operational workflows.

Experience with data preparation, feature engineering, and model development.

Ability to analyze data and communicate insights clearly.

Ability to troubleshoot technical issues, communicate recommendations clearly, and work effectively in team-based delivery environments.

Experience supporting AI governance practices, including model documentation, validation, monitoring, version control, and responsible AI considerations.

Ability to work across data science, data engineering, cloud, security, and client stakeholder teams to translate analytical prototypes into scalable, maintainable solutions.

What Would Be Nice to Have:

2+ years of hands-on experience with the Databricks platform.

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.

The annual salary range for this position is $113,000.00-$188,000.00. Compensation decisions depend on a wide range of factors, including but not limited to skill sets, experience and training, security clearances, licensure and certifications, and other business and organizational needs.

What We Offer:

Guidehouse offers a comprehensive, total rewards package that includes competitive compensation and a flexible benefits package that reflects our commitment to creating a diverse and supportive workplace.

About Guidehouse

Guidehouse is an Equal Opportunity Employer–Protected Veterans, Individuals with Disabilities or any other basis protected by law, ordinance, or regulation.

Guidehouse will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of applicable law or ordinance including the Fair Chance Ordinance of Los Angeles and San Francisco.

If you have visited our website for information about employment opportunities, or to apply for a position, and you require an accommodation, please contact Guidehouse Recruiting at 1-571-633-1711 or via email at RecruitingAccommodation@guidehouse.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodation.

All communication regarding recruitment for a Guidehouse position will be sent from Guidehouse email domains including @guidehouse.com or guidehouse@myworkday.com. Correspondence received by an applicant from any other domain should be considered unauthorized and will not be honored by Guidehouse. Note that Guidehouse will never charge a fee or require a money transfer at any stage of the recruitment process and does not collect fees from educational institutions for participation in a recruitment event. Never provide your banking information to a third party purporting to need that information to proceed in the hiring process.

If any person or organization demands money related to a job opportunity with Guidehouse, please report the matter to Guidehouse’s Ethics Hotline. If you want to check the validity of correspondence you have received, please contact recruiting@guidehouse.com. Guidehouse is not responsible for losses incurred (monetary or otherwise) from an applicant’s dealings with unauthorized third parties.

Guidehouse does not accept unsolicited resumes through or from search firms or staffing agencies. All unsolicited resumes will be considered the property of Guidehouse and Guidehouse will not be obligated to pay a placement fee.