{"id":2747897,"url":"https://alion.io/job/guidehouse-fraud-aiml-data-scientist","title":"Fraud AI/ML Data Scientist","company":{"id":4179,"name":"Guidehouse","domain":"guidehouse.com","url":"https://alion.io/company/guidehouse","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":89,"open_postings":136,"ghost_share":0.007,"stale_share":0.61,"repost_share":0.022,"time_to_fill_p50_days":21,"computed_at":"2026-10-17T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Antonio, United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":80000,"max":133000,"currency":"USD","period":"year","gross":null,"usd_annual":133000},"salary_estimate":null,"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Amazon CloudWatch","optional":false},{"name":"Amazon ECS","optional":false},{"name":"Amazon EKS","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"Apache Iceberg","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"AWS Glue","optional":false},{"name":"AWS Lambda","optional":false},{"name":"AWS Step Functions","optional":false},{"name":"Embeddings","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"NumPy","optional":false},{"name":"OCR","optional":false},{"name":"OpenSearch","optional":false},{"name":"Pandas","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Semantic Search","optional":false},{"name":"Semantic Search","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"Time Series Forecasting","optional":false},{"name":"Agentic Workflows","optional":true},{"name":"Explainable AI","optional":true},{"name":"Hybrid Search","optional":true},{"name":"IAM","optional":true},{"name":"Knowledge Graph","optional":true},{"name":"Kubernetes","optional":true},{"name":"Least Privilege","optional":true},{"name":"LLM Guardrails","optional":true},{"name":"Multimodal AI","optional":true},{"name":"Prompt Engineering","optional":true},{"name":"RAG","optional":true}],"status":"live","first_seen_at":"2026-10-16T23:03:49Z","employer_posted_date":"2026-10-16","last_verified_at":"2026-10-17T04:04:31Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Job Family:\nData Science & AnalysisTravel Required:\nUp to 10%Clearance Required:\nAbility to Obtain Public TrustWhat You Will Do:\nPartner with stakeholders to define and deliver AI, machine learning, and advanced analytics use cases, translating business needs into scalable data science solutions.\nDesign and develop machine learning models and analytical approaches to support search, discovery, anomaly detection, fraud detection, and insight generation across structured and unstructured data.\nDevelop anomaly and fraud detection analyses using supervised, unsupervised, semi-supervised, statistical, and graph-based techniques, including outlier detection, behavioral profiling, risk scoring, pattern detection, and relationship analysis.\nUse Generative AI and foundation models to enhance anomaly and fraud detection workflows through alert enrichment, case summarization, contextual analysis, evidence synthesis, pattern explanation, investigative hypothesis generation, and analyst decision support.\nBuild and implement natural language processing, semantic search, entity resolution, and relationship analytics capabilities to enable advanced information retrieval and identification of suspicious patterns and connections.\nLeverage document-based data, including OCR/ICR outputs, metadata, images, extracted fields, and free text, to support downstream analytics, search, anomaly detection, and fraud analysis.\nCollaborate with data engineers, cloud engineers, investigators, and business stakeholders to integrate models and analytical capabilities into production environments using AWS-native services.\nDevelop and operationalize data science solutions within an AWS data lakehouse, including scalable data preparation, feature engineering, model training, inference, monitoring, and analytics.\nDevelop model evaluation frameworks, confidence and risk scoring, explainability, traceability, and human-in-the-loop review approaches to ensure AI outputs are transparent, actionable, and suitable for investigative and operational use.\nEvaluate anomaly and fraud detection models using appropriate measures, including precision, recall, F1 score, false-positive rate, detection rate, ranking quality, and business impact.\nSupport the development of dashboards, reporting, alerting, and investigative workflows that drive operational insights and informed decision-making.\nOperate within an Agile delivery model, contributing to sprint planning, experimentation, model iteration, and incremental solution delivery.\nCommunicate findings, risk indicators, model limitations, and recommendations clearly to technical and non-technical audiences, including client stakeholders.\nContribute to solution design, proposal support, technical documentation, and thought leadership in AI, analytics, anomaly detection, and fraud detection.\nWhat You Will Need:\nBachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field.\nA minimum of 4 years of experience in data science, machine learning, artificial intelligence, or applied analytics roles.\nU.S. Citizenship required and the ability to obtain and maintain a Public Trust clearance.\nExperience developing and applying machine learning models in one or more of the following areas: Natural Language Processing (NLP)\n Semantic search or information retrieval\n Entity resolution or relationship modeling\n Anomaly or outlier detection\n Fraud, risk, waste, abuse, or suspicious-pattern detection\n Graph analytics or network analysis\n\nSkills and experience designing or implementing anomaly and fraud detection analyses using methods such as classification, clustering, isolation-based techniques, autoencoders, time-series analysis, behavioral analytics, link analysis, rules-based detection, or ensemble modeling.\nDemonstrated competency working with AWS-native data, analytics, AI, and machine learning services, such as Amazon S3, AWS Glue, AWS Lake Formation, Amazon Athena, Amazon EMR, Amazon Redshift, Amazon SageMaker, Amazon Bedrock, AWS Lambda, AWS Step Functions, Amazon OpenSearch Service, Amazon ECS or Amazon EKS, and Amazon CloudWatch.\nDemonstrated competency working with AWS data lakehouse architectures, including Amazon S3-based data lakes, Apache Iceberg or similar open table formats, centralized metadata catalogs, governed data access, schema evolution, partitioning, data quality, and scalable query and transformation patterns.\nDemonstrated competency using Generative AI, large language models, or foundation models for anomaly and fraud detection analysis, including alert enrichment, investigative summarization, contextual reasoning, evidence synthesis, pattern explanation, and analyst assistance.\nExperience working with large-scale structured and unstructured data, particularly document-based datasets such as text, PDFs, images, extracted fields, and metadata.\nExperience using metadata, engineered features, embeddings, event or transaction histories, and relationship data to support analytics and modeling.\nStrong proficiency in Python for data science and machine learning, including libraries such as Pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow, along with strong SQL skills.\nExperience building scalable data processing and machine learning pipelines using AWS-native services and open-source frameworks such as Apache Spark.\nExperience integrating models into production environments through APIs, batch pipelines, event-driven workflows, streaming pipelines, or embedded analytics applications.\nUnderstanding of model evaluation, validation, monitoring, drift detection, bias assessment, explainability, and performance measurement.\nUnderstanding of operational challenges in anomaly and fraud detection, including class imbalance, changing patterns, false positives, data leakage, concept drift, and feedback-loop design.\nAbility to apply responsible AI, privacy, security, and governance practices when using Generative AI with sensitive or regulated data.\nStrong communication skills and the ability to translate analytical outputs, detected risks, and model results into actionable insights.\nExperience working in cross-functional, matrixed teams in an Agile environment.\nWhat Would Be Nice To Have:\nExperience developing production-grade anomaly detection, fraud detection, waste and abuse analytics, risk-scoring, or investigative decision-support solutions.\nExperience using Amazon Bedrock foundation models or comparable enterprise Generative AI capabilities for analytics, anomaly detection, fraud investigation, or case-management workflows.\nExperience implementing Retrieval-Augmented Generation (RAG), prompt engineering, agentic workflows, guardrails, foundation-model evaluation, and responsible AI controls for enterprise use cases.\nExperience building AI-enabled search solutions, including semantic search, hybrid search, document retrieval, embeddings, and ranking models using AWS-native services.\nExperience with multimodal data processing involving text, images, documents, metadata, and other data types.\nFamiliarity with OCR/ICR and document intelligence pipelines using services such as Amazon Textract and Amazon Bedrock.\nExperience using Amazon SageMaker for feature engineering, model development, training, deployment, monitoring, and machine learning lifecycle management.\nExperience using Amazon OpenSearch Service, graph databases, or graph-processing frameworks for relationship mapping, link analysis, and suspicious-network detection.\nExperience developing explainable AI solutions, including confidence scoring, reason codes, feature attribution, evidence traceability, and analyst-friendly explanations.\nExperience designing analytics dashboards, alert-management interfaces, investigative reporting, or case-triage solutions for end users.\nKnowledge of AWS security and governance practices, including IAM, encryption, logging, data classification, least-privilege access, and handling sensitive or regulated information.\nPrevious experience supporting federal clients or working in regulated environments.\nConsulting experience or experience in a client-facing delivery role strongly preferred.\nExperience supporting training, user enablement, or adoption of analytics capabilities across teams.\nFamiliarity with graph-based analytics, ontology-driven models, knowledge graphs, or relationship mapping.\nThe annual salary range for this position is $80,000.00-$133,000.00. 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:\nGuidehouse 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.\nBenefits include:\nMedical, Rx, Dental & Vision Insurance\n\nPersonal and Family Sick Time & Company Paid Holidays\n\nParental Leave\n\n401(k) Retirement Plan\n\nGroup Term Life and Travel Assistance\n\nVoluntary Life and AD&D Insurance\n\nHealth Savings Account, Health Care & Dependent Care Flexible Spending Accounts\n\nTransit and Parking Commuter Benefits\n\nShort-Term & Long-Term Disability\n\nTuition Reimbursement, Personal Development, Certifications & Learning Opportunities\n\nEmployee Referral Program\n\nCorporate Sponsored Events & Community Outreach\n\nCare.com annual membership\n\nEmployee Assistance Program\n\nSupplemental Benefits via Corestream (Critical Care, Hospital Indemnity, Accident Insurance, Legal Assistance and ID theft protection, etc.)\n\nPosition may be eligible for a discretionary variable incentive bonus\n\nAbout Guidehouse\nGuidehouse is an Equal Opportunity Employer-Protected Veterans, Individuals with Disabilities or any other basis protected by law, ordinance, or regulation.\nGuidehouse 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.\nIf 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 . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodation.\nAll communication regarding recruitment for a Guidehouse position will be sent from Guidehouse email domains including @guidehouse.com or . 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.\nIf 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 . Guidehouse is not responsible for losses incurred (monetary or otherwise) from an applicant’s dealings with unauthorized third parties.\nGuidehouse 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.","description_format":"text","description_chars":11780,"description_truncated":false,"requirements":{"experience_years_min":4,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":true,"languages":[]},"benefits":["Parental leave","Retirement plans","Vision insurance"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Digital Government","IT Consulting & Digital Transformation","Management Consulting"],"lifecycle":[{"event":"open","at":"2026-10-16T23:03:49Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 24 · green card filings: 14","filings_12m":24,"filings_prev_12m":23,"green_card_filings_12m":14,"median_offered_wage_usd":132500,"route":null,"cap_exempt":false,"checked_at":"2026-10-15T11:24:14+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)","US Department of Labor: PERM disclosure data (green cards)"],"filings_for_role_12m":7}],"liveness":{"score":63,"band":"ok","label":"Likely open","p_open":1,"p_active":0.632,"p_room":1,"age_days":0,"expected_fill_days":21,"reasons":["conf:1","stale_co","velocity","win:early","comp:brand"],"computed_at":"2026-10-17T05:46:00Z"},"pay":{"stated_usd_annual":133000,"is_top_pay":false},"html_url":"https://alion.io/job/guidehouse-fraud-aiml-data-scientist","json_url":"https://alion.io/job/guidehouse-fraud-aiml-data-scientist.json","meta":{"generated_at":"2026-10-17T17:30:09Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":24028,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-18T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":4179},"rest":"https://alion.io/mcp/rest/get_company?id=4179"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fguidehouse-fraud-aiml-data-scientist"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fguidehouse-fraud-aiml-data-scientist"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fguidehouse-fraud-aiml-data-scientist"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/guidehouse-fraud-aiml-data-scientist\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fguidehouse-fraud-aiml-data-scientist"}]}