Job Family:
Data Science Consulting
Travel Required:
Clearance Required:
Partner with stakeholders to define and deliver AI/analytics use cases, translating business needs into scalable data science solutions.
Design and develop machine learning models and analytical approaches to support search, discovery, and insight generation across structured and unstructured data.
Build and implement NLP, semantic search, and entity resolution capabilities to enable advanced information retrieval and relationship analysis.
Leverage document-based data (e.g., OCR/ICR outputs, metadata, and free text) to extract insights and support downstream analytics and search solutions.
Collaborate with data engineers to integrate models into production environments, including Palantir Foundry, Databricks, and AWS-based platforms.
Develop model evaluation frameworks, confidence scoring, and explainability approaches to ensure transparency and usability of AI outputs.
Support the development of analytics, reporting, and dashboards to drive operational insights and decision-making.
Operate within an Agile delivery model, contributing to sprint planning, experimentation, and iterative solution delivery.
Communicate findings and recommendations clearly to both technical and non-technical audiences, including client stakeholders.
Contribute to solution design, proposal support, and thought leadership in AI/analytics capabilities
What You Will Need:
A Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field is required
A minimum of FOUR (4) years of experience in data science, machine learning, or applied analytics roles
U.S. Citizenship required and ability to obtain and maintain a Public Trust clearance.
Experience developing and applying machine learning models, including:
Natural Language Processing (NLP)
Semantic search or information retrieval
Entity resolution or relationship modeling
Experience working with large-scale structured and unstructured data, particularly document-based datasets (e.g., text, PDFs, images).
Experience leveraging metadata and extracted features to support analytics and modeling.
Strong proficiency in Python for data science and machine learning (e.g., Pandas, Scikit-learn, PyTorch or TensorFlow) and solid SQL skills.
Experience working with Databricks and/or Spark-based environments for scalable data processing.
Familiarity with AWS cloud services for data access, processing, or model deployment.
Experience working with data lake or lakehouse architectures (e.g., AWS S3, Databricks), including querying and transforming large-scale datasets.
Experience integrating models into production environments (e.g., APIs, batch pipelines, or embedded analytics platforms).
Understanding of model evaluation, validation, and performance metrics.
Strong communication skills and ability to translate analytical outputs into actionable insights.
Experience working in cross-functional, matrixed teams in an Agile environment.
What Would Be Nice To Have:
- Experience supporting fraud detection, risk analytics, or investigative use cases, including development of models or analytics to identify anomalous behavior, patterns, or suspicious activity.
- Familiarity with law enforcement, regulatory, or compliance-focused analytics environments, including data used in investigations, intelligence analysis, or case management workflows.
- Experience working with abuse-related datasets or use cases (e.g., financial fraud, identity theft, program integrity, cyber abuse), including applying NLP, entity resolution, or graph analytics to detect and analyze abusive or fraudulent behavior.
- Understanding of investigative analytics techniques, including link analysis, network/graph-based modeling, and relationship mapping to support law enforcement or fraud detection initiatives.
- Experience working with Palantir Foundry and/or Palantir AIP, particularly in support of AI-enabled search or analytics workflows.
- Consulting experience strongly preferred.
- Experience building AI-enabled search solutions, including semantic search, document retrieval, and ranking models.
- Experience with multimodal data processing, including text and image-based analytics.
- Familiarity with OCR/ICR pipelines and document intelligence use cases.
- Experience with enterprise ML platforms (e.g., AWS SageMaker, Databricks Machine Learning) for model development, deployment, and lifecycle management.
- Experience developing explainable AI (XAI) solutions, including confidence scoring and traceability of results.
- Experience designing analytics dashboards or reporting solutions for end users.
- Previous experience supporting federal clients or working in regulated environments.
- Experience in a consulting firm and/or client-facing delivery role.
- Experience supporting training, user enablement, or scaling analytics capabilities across teams.
- Familiarity with graph-based analytics, ontology-driven models, or relationship mapping.
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.
Benefits include:
Medical, Rx, Dental & Vision Insurance
Personal and Family Sick Time & Company Paid Holidays
Position may be eligible for a discretionary variable incentive bonus
Parental Leave and Adoption Assistance
401(k) Retirement Plan
Basic Life & Supplemental Life
Health Savings Account, Dental/Vision & Dependent Care Flexible Spending Accounts
Short-Term & Long-Term Disability
Student Loan PayDown
Tuition Reimbursement, Personal Development & Learning Opportunities
Skills Development & Certifications
Employee Referral Program
Corporate Sponsored Events & Community Outreach
Emergency Back-Up Childcare Program
Mobility Stipend
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 [email protected]. 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 [email protected]. 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 [email protected]. 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.
Skills Required
- Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or related field
- Minimum of four (4) years of experience in data science, machine learning, or applied analytics roles
- U.S. Citizenship and ability to obtain and maintain a Public Trust clearance
- Experience developing and applying machine learning models, including NLP, semantic search, and entity resolution
- Experience working with large-scale structured and unstructured data, particularly document-based datasets (text, PDFs, images)
- Experience leveraging metadata and extracted features to support analytics and modeling
- Strong proficiency in Python for data science and machine learning (Pandas, Scikit-learn, PyTorch or TensorFlow) and solid SQL skills
- Experience working with Databricks and/or Spark-based environments for scalable data processing
- Familiarity with AWS cloud services for data access, processing, or model deployment
- Experience with data lake or lakehouse architectures (e.g., AWS S3, Databricks) including querying and transforming large datasets
- Experience integrating models into production environments (APIs, batch pipelines, or embedded analytics platforms)
- Understanding of model evaluation, validation, and performance metrics
- Strong communication skills and ability to translate analytical outputs into actionable insights
- Experience working in cross-functional, matrixed teams in an Agile environment
- Experience supporting fraud detection, risk analytics, or investigative use cases
- Familiarity with law enforcement, regulatory, or compliance-focused analytics environments
- Experience with Palantir Foundry and/or Palantir AIP
- Experience building AI-enabled search solutions, including semantic search, document retrieval, and ranking models
- Experience with multimodal data processing (text and image) and OCR/ICR pipelines
- Experience with enterprise ML platforms (e.g., AWS SageMaker, Databricks Machine Learning) for model lifecycle management
- Experience developing explainable AI (XAI) solutions, including confidence scoring and traceability
- Previous experience supporting federal clients or working in regulated environments
- Consulting experience and client-facing delivery experience
- Experience designing analytics dashboards or reporting solutions for end users
- Familiarity with graph-based analytics, ontology-driven models, or relationship mapping
Guidehouse Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Guidehouse and has not been reviewed or approved by Guidehouse.
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Healthcare Strength — Feedback suggests the benefits package includes broad medical, dental, vision, prescription, life, and disability coverage, which is often seen as a strong foundational offering. Access to HSA/FSA options further supports day-to-day healthcare and dependent-care needs.
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Parental & Family Support — Feedback suggests parental leave and adoption assistance are available, alongside an emergency back-up childcare program. These offerings indicate meaningful support for employees managing family responsibilities.
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Wellbeing & Lifestyle Benefits — Feedback suggests flexible work options and counseling/EAP-style support are part of the broader rewards mix. Additional lifestyle-oriented perks like community events and referral programs are also described as available in some contexts.
Guidehouse Insights
What We Do
Guidehouse is a leading global provider of consulting services to the public sector and commercial markets, with broad capabilities in management, technology, and risk consulting. By combining our public and private sector expertise, we help clients address their most complex challenges and navigate significant regulatory pressures focusing on transformational change, business resiliency, and technology-driven innovation. Across a range of advisory, consulting, outsourcing, and digital services, we create scalable, innovative solutions that help our clients outwit complexity and position them for future growth and success. The company has more than 12,000 professionals in over 50 locations globally. Guidehouse is a Veritas Capital portfolio company, led by seasoned professionals with proven and diverse expertise in traditional and emerging technologies, markets, and agenda-setting issues driving national and global economies.
