Pay
In line with similar jobs
$113K–$188K against $118K–$195K, the middle half of what similar US postings state.
From 3,817 postings in the last year. Stated ranges, not salaries paid.
US - Remote (Any location)
Live, first seen by us 86 days agoFamiliarity 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.Read the full posting
Listed location: US - Remote (Any location)Read the full posting
Employment type in the employer’s posting: Full timeFrom the employer’s posting
Develop, train, and evaluate machine learning and statistical models on Databricks
Prepare, clean, and maintain datasets for modeling and analysis
Design feature engineering workflows and model training pipelines in Databricks and MLflow
Monitor deployed models for drift, data quality, and performance; recommend retraining
Translate business requirements into analytical approaches and data science solutions
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.
Design reusable feature engineering workflows and model training pipelines using Databricks notebooks, workflows, and MLflow.
Monitor deployed models for performance, drift, data quality, usage patterns, and operational issues; recommend retraining, tuning, or retirement actions as needed.
Translate business requirements into analytical approaches, models, and data science solutions.
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.
2+ years of hands-on experience with the Databricks platform.
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.
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.
Guidehouse is an Equal Opportunity Employer–Protected Veterans, Individuals with Disabilities or any other basis protected by law, ordinance, or regulation.
In the employer’s words · Read in context
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
In line with similar jobs
$113K–$188K against $118K–$195K, the middle half of what similar US postings state.
From 3,817 postings in the last year. Stated ranges, not salaries paid.
Day 86
Up longer than most. Similar jobs usually come down between day 8 and day 59.
Well past Guidehouse’s usual: its jobs come down by about day 30.
From 11,372 similar postings that came down, and 149 of Guidehouse’s. Coming down is not always a hire.
102 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
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.
- 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.
- 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.
- 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.
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:
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.
- 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.
- 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.
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.
- 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.
- 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 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.
- 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.
Complete your application on guidehouse.wd1.myworkdayjobs.com. The employer’s form will show what is required.
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New Data Scientist postings at the employers we follow are down 6% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
Job Family:
Data Science & Analysis, Data Science Consulting
Travel Required:
Clearance Required:
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 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.
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.
Selected passages from the saved posting. Check the full description for conditions and exceptions.
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.
US - Remote (Any location)
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.
No clear work-authorization passage found. Eligibility is unconfirmed.