Data Scientist

Hawk

. Tune and optimize detection models and thresholds against customers’ live transaction data .

Posted 10/30/2026full-timeLondon • United KingdomMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in data science with a focus on AML, fraud detection, and transaction monitoring, leveraging strong analytical skills to optimize detection models and present findings to clients. Capable of translating model performance into actionable business value while maintaining compliance and addressing customer-specific needs.

Highest-signal resume keywords

Data Science ExpertiseAML And Fraud DetectionPython And SQL ProficiencyCustomer-Facing Presentation SkillsTransaction Monitoring Knowledge

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ScienceModel OptimizationTransaction MonitoringFraud DetectionAnalytical Findings ConversionModel Performance TranslationBacktestingConfiguration ChangesPattern Drift InvestigationFalse-Positive Cost Analysis

Soft Skills

Ownership MentalityComfort With AmbiguityCustomer EngagementCommunication SkillsProblem-Solving

Tools & Technologies

Production ML ToolingData Analysis ToolsStatistical SoftwareModel Validation ToolsHybrid Detection Approaches

Industry Keywords

Financial Crime AnalyticsComplianceRisk ManagementExplainable AIPayments Fraud Detection

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Tune and optimize detection models and thresholds against customers’ live transaction data
Investigate missed cases, alert quality, and pattern drift
Convert analytical findings into tuning or configuration changes
Build customer-facing analyses showing investigator productivity gains, false-positive cost reduction, and detection improvements
Present findings directly to customers and defend methodology to their data science or compliance teams
Answer customer questions about model decisions
Partner with regional Customer Value Partners on account strategy and value realization
Feed customer patterns and findings into Hawk’s model and product functions
Distinguish customer-specific tuning needs from systemic product gaps
Document tuning decisions for audit and regulatory review
Validate model changes through backtesting, sample review, and sign-off discipline

Requirements

What you’ll need

5-7 years as a data scientist in a customer-facing role
Experience presenting analysis and defending model decisions directly to clients
Real experience in AML, fraud detection, or financial crime analytics
Understanding of transaction monitoring, typologies, and investigator false-positive costs
Strong hands-on skills in Python, SQL, and production ML tooling
Ability to make sound model-change decisions under ambiguity and determine when human review is needed
Ability to act as the technical voice with customers’ risk, compliance, or data science stakeholders
Track record of translating model performance into actionable business value
Comfort with ambiguity and live production systems
Ownership mentality and ability to investigate drifting account detection performance
Fluent English speaking, reading, and writing
Ability to work onsite 2-3 days per week in a hybrid setup
Experience specifically in transaction monitoring or payments fraud detection at a bank, payment provider, or vendor serving them (bonus)
Familiarity with explainable AI and rules-based hybrid detection approaches (bonus)

Benefits

Comp & perks

Opportunities to grow professionally and make a difference in the world
Hybrid work model with onsite work 2-3 days per week
Flexible choice among multiple office locations in the hybrid setup
AI Notetaker interview recording and transcription with voluntary consent; consent can be withdrawn without impact on the application