Aml Model Validation Jobs in Washington (NOW HIRING)

K2 Integrity is seeking an experienced compliance professional with deep subject matter expertise in transaction monitoring, sanctions screening, and blockchain analytics program design (rule setting, governance, pre/post implementation testing) and model risk management/ validation. Sitting within FCRM Advisory, this individual will serve as the practice’s go-to subject‑matter expert and project execution lead across several cross‑functional areas (traditional finance, fintech, crypto verticals). This individual will be responsible for designing and optimizing detection rules, validating model performance, documenting methodologies, and ensuring compliance with applicable regulatory requirements, including the NewYork Department of Financial Services (NYDFS) Part504 annual certification requirements and other applicable U.S.AML/BSA, OFAC, FinCEN, FFIEC, and industry best practices.

This is a rare seat for a practitioner who is genuinely bilingual across traditional finance (tradfi) and crypto. You will validate the analytics that banks, stablecoin issuers, and payments firms rely on to detect financial crime — from Actimize and Oracle Mantas to Chainalysis, TRM Labs, and Elliptic — and translate a fragmented set of client needs into a consistent, defensible, and scalable methodology that the firm can deploy at speed and at margin.

What sets this role apart: we are looking for someone who can do both tradfi and crypto — not one or the other. The ideal hire pairs deep, hands‑on experience validating blockchain‑analytics rule settings with rigorous TM rule design and coverage assessment discipline, has already built a scalable methodology, and actively leverages AI to deliver better, faster, and more defensible outcomes.

This is a hybrid role out of our D.C. office.

• 7+ years of experience in AML model validation, transaction monitoring rule design, sanctions screening, model risk management, and financial crimes compliance, with at least 2 years of hands‑on experience in blockchain‑analytics settings/model review, including validating and configuring blockchain‑analytics rule settings (Chainalysis, TRM Labs, Elliptic, or comparable)
• Bachelor’s degree in a relevant field or international equivalent
• Strong knowledge of model risk management standards / regulatory methodological fluency including: OCC Bulletin 2026-13 (Model Risk Management: Revised Guidance) and its risk-based, principles-based approach (andSR11-7 / OCC2011-12) DFS Part504 FFIECBSA/AML Examination Manual OFAC “Framework for OFAC Compliance Commitments” and sanctions screening expectations
• A mixture of consulting and in‑house expertise, with hands‑on experience across both crypto/digital‑asset firms and traditional financial institutions
• Demonstrated experience performing coverage assessments tailored to a client’s risk profile, designing transaction monitoring scenarios, rule implementation, and alert optimization methodologies
• Demonstrated experience in sanctions screening rule tuning and list governance
• Experience supporting regulatory examinations and annual compliance certifications
• Excellent analytical, documentation, and stakeholder management skills
• Hands‑on platform experience across traditional TM, sanctions screening, and blockchain analytics systems
• Strong technical and data skills, including ability to independently write and review queries to support ATL/BTL testing, rule replication, and data‑lineage validation
• Strong understanding of statistical validation techniques, data analysis, and model performance metrics
• Familiarity with Snowflake, Databricks, or comparable warehouses; Tableau/PowerBI for outcomes analysis and reporting
• AI governance mindset: thinks about AI governance and is comfortable reasoning about how model‑risk principles apply to AI/ML systems preferred
• Prior experience with fraud risk models and graph analytics preferred
• AI/ML literacy sufficient to validate ML‑based TM or fraud models under model‑risk principles (bias, drift, explainability) preferred
• A portable book of work or referral relationships from a prior industry or consulting seat preferred

• Own MRM and model validation engagements end‑to‑end — pre‑and post‑implementation testing, ongoing validation, and periodic re‑validation — aligned to current interagency guidance, including OCC Bulletin2026-13 and state standards such as NY‑DFS Part504
• Apply a risk-based, materiality‑driven approach consistent with OCC Bulletin2026-13, tailoring the depth of validation and effective challenge to the complexity and materiality of each model and the client’s risk profile
• Develop and maintain model governance documentation, validation reports, and audit‑ready workpapers

• Hands‑on validation, configuration, and tuning of tools such as Chainalysis (KYT), TRM Labs, Elliptic (Lens), and Merkle Science, including rule library configuration, exposure/typology thresholds, risk‑scoring logic, and integration into TM and case‑management workflows
• Serve as the firm’s credible SME on validating crypto models and blockchain‑analytics settings

• Design and calibrate rule sets and perform coverage assessments that map TM/sanctions coverage to the client’s specific business activity, products, customers, and geographies (never a one‑size template)
• Lead threshold calibration, above‑/below‑the‑line (ATL/BTL) testing, and pre‑and post‑implementation validation, through to ongoing monitoring
• Translate risk assessments into defensible detection scenarios and document the rationale for coverage decisions
• Partner with Compliance, Financial Crimes, Risk, Data Science, Product, and Engineering teams to implement and enhance monitoring and screening capabilities

• Validate and tune sanctions screening systems — list management, fuzzy‑matching parameters, threshold tuning, filter logic testing, and name‑matching algorithm review (ideally with experience across a variety of vendors)

• Scalable methodology ownership: build, maintain, and continuously improve a consistent, repeatable methodology across MRM, validation, TM design, and sanctions tuning
• AI‑enabled delivery: leverage AI to improve the speed, consistency, and defensibility of testing, sampling, and documentation, positioning the practice for the emerging AI model‑validation adjacency
• Team development and cross‑training: upskill existing resources to scale delivery
• Client‑facing polish: present findings with authority to CCO/BSAO stakeholders, boards, and regulators
• Market Eminence: Monitor emerging financial crime typologies, regulatory guidance, and industry practices to continuously enhance detection capabilities, and contribute to firm thought leadership as needed