AML/Sanctions Data Scientist – Associate

PwC

PwC financial crime data scientist applying SQL, Python, machine learning, NLP, and LLMs. Supporting AML analytics and client engagements within the Financial Crime Unit.

Posted 8/10/2026full-timeSeattle • District of Columbia, Massachusetts, North Carolina, Pennsylvania, Washington • 🇺🇸 United StatesJuniorMid-Level💰 $63,000 - $140,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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

Demonstrates expertise in SQL and Python for data analysis, with a strong foundation in machine learning concepts and algorithms. Engages effectively with clients while upholding professional standards in financial crime and fraud analytics.

Highest-signal resume keywords

SQL Data QueryingAdvanced Python SkillsMachine Learning Model DeploymentFinancial Crime AnalyticsCI/CD Pipelines for Data Science

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data AnalysisMachine LearningNLPData ManipulationStatistical AnalysisComplex Data QueriesEvaluation MetricsAgentic AI FrameworksStructured and Unstructured Data HandlingBuilding Machine Learning Models

Soft Skills

Client EngagementAnalytical ThinkingAdaptabilityTeam CollaborationStrategic Insight Development

Tools & Technologies

Scikit-learnXGBoostHugging Face TransformersCI/CD ToolsData Processing Tools

Industry Keywords

Financial CrimeAMLFraud AnalyticsData ScienceMachine Learning Concepts

Tech Stack

Tools & technologies

PythonScikit-LearnSQL

About the role

Key responsibilities & impact

Utilize analytical techniques to address financial crime issues
Engage with clients to foster meaningful professional relationships
Apply SQL and Python for data analysis and problem-solving
Explore machine learning, NLP, and LLMs in relevant projects
Contribute to team efforts while enhancing personal technical skills
Adapt to complex situations and develop strategic insights
Participate in research to support project objectives
Uphold professional standards and ethical guidelines

Requirements

What you’ll need

Bachelor's Degree in Computer and Information Science, Computer and Information Science & Accounting, Economics, Economics and Finance, Economics and Finance & Technology, Engineering, Operations Management/Research, Statistics, Mathematics, Data Processing/Analytics/Science or related field
1 year of experience in data science/machine learning
Interest in financial crime, AML, and fraud analytics
Skilled in SQL for complex data queries
Advanced Python skills for data manipulation
Experience building and deploying machine learning models
Understanding of machine learning concepts and algorithms
Comfort working with structured and unstructured data
Familiarity with agentic AI frameworks
Hands-on experience with CI/CD pipelines for data science
Proficiency in SQL and Python
Basic understanding of machine learning algorithms and evaluation metrics
Exposure to scikit-learn, XGBoost, and Hugging Face Transformers
Other quantitative fields of study may be considered
Ability to travel up to 60%

Benefits

Comp & perks

Annual discretionary bonus
Medical insurance
Dental insurance
Vision insurance
401(k)
Holiday pay
Vacation
Personal and family sick leave