Fraud AI/ML Data Scientist

🔥 2 minutes ago

🇺🇸 United States – Remote

💵 $80k - $133k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

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Guidehouse

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 2018

🏥 Healthcare

🎖️ Defense

📦 Logistics

💰 Grant on 2023-02

Healthcare • Defense • Logistics

Guidehouse is a global consultancy offering advisory, digital, and managed services across commercial and public sectors. It is purpose-built to support industries such as national security, financial services, healthcare, energy, and infrastructure. Guidehouse collaborates with leaders to navigate complexity and drives transformational changes that impact the future. Their expertise spans data analytics, digital technologies, risk management, and more, with a strong emphasis on sustainability and innovation.

📋 Description

• Partner with stakeholders to define and deliver AI, machine learning, and advanced analytics use cases • Translate business needs into scalable data science solutions • Design and develop machine learning models for search, discovery, anomaly detection, fraud detection, and insight generation • Develop anomaly and fraud detection analyses using supervised, unsupervised, semi-supervised, statistical, and graph-based techniques • Use Generative AI and foundation models for alert enrichment, case summarization, contextual analysis, evidence synthesis, pattern explanation, hypothesis generation, and analyst decision support • Build NLP, semantic search, entity resolution, and relationship analytics capabilities • Leverage document-based data including OCR/ICR outputs, metadata, images, extracted fields, and free text • Collaborate with data engineers, cloud engineers, investigators, and business stakeholders to integrate models into production using AWS-native services • Develop and operationalize data science solutions within an AWS data lakehouse • Build model evaluation frameworks, confidence and risk scoring, explainability, traceability, and human-in-the-loop review approaches • Evaluate models using precision, recall, F1 score, false-positive rate, detection rate, ranking quality, and business impact • Support dashboards, reporting, alerting, and investigative workflows • Operate in an Agile delivery model through sprint planning, experimentation, model iteration, and incremental delivery • Communicate findings, risk indicators, model limitations, and recommendations to technical and non-technical audiences • Contribute to solution design, proposal support, technical documentation, and thought leadership

🎯 Requirements

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field • Minimum of 4 years of experience in data science, machine learning, artificial intelligence, or applied analytics roles • U.S. Citizenship required • Ability to obtain and maintain a Public Trust clearance • Experience developing and applying machine learning models in NLP, semantic search/information retrieval, entity resolution/relationship modeling, anomaly/outlier detection, fraud/risk/waste/abuse detection, or graph/network analysis • Experience designing or implementing anomaly and fraud detection analyses using classification, clustering, isolation-based techniques, autoencoders, time-series analysis, behavioral analytics, link analysis, rules-based detection, or ensemble modeling • Competency with AWS-native services including 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/EKS, and Amazon CloudWatch • Competency with AWS data lakehouse architectures, Apache Iceberg or similar open table formats, metadata catalogs, governed data access, schema evolution, partitioning, data quality, and scalable query/transformation patterns • Competency using Generative AI, large language models, or foundation models for anomaly and fraud detection • Experience with large-scale structured and unstructured document-based data • Experience using metadata, engineered features, embeddings, event/transaction histories, and relationship data • Strong Python proficiency, including Pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow • Strong SQL skills • Experience building scalable data processing and machine learning pipelines using AWS-native services and Apache Spark • Experience integrating models into production through APIs, batch pipelines, event-driven workflows, streaming pipelines, or embedded analytics applications • Understanding of model evaluation, validation, monitoring, drift detection, bias assessment, explainability, and performance measurement • Understanding of anomaly and fraud detection challenges including class imbalance, changing patterns, false positives, data leakage, concept drift, and feedback-loop design • Ability to apply responsible AI, privacy, security, and governance practices with sensitive or regulated data • Strong communication skills and ability to translate analytical outputs into actionable insights • Experience working in cross-functional, matrixed teams in an Agile environment

🏖️ Benefits

• Medical, Rx, Dental & Vision Insurance • Personal and Family Sick Time & Company Paid Holidays • Parental Leave • 401(k) Retirement Plan • Group Term Life and Travel Assistance • Voluntary Life and AD&D Insurance • Health Savings Account, Health Care & Dependent Care Flexible Spending Accounts • Transit and Parking Commuter Benefits • Short-Term & Long-Term Disability • Tuition Reimbursement, Personal Development, Certifications & Learning Opportunities • Employee Referral Program • Corporate Sponsored Events & Community Outreach • Care.com annual membership • Employee Assistance Program • Supplemental Benefits via Corestream (Critical Care, Hospital Indemnity, Accident Insurance, Legal Assistance and ID theft protection, etc.) • Position may be eligible for a discretionary variable incentive bonus • Flexible benefits package