Data Scientist (AML, Global Transaction Monitoring)

Insight Global is seeking a Data Scientist to join a top bank within their Global Transaction Monitoring team to support the development and enhancement of Anti-Money Laundering (AML) models used to identify suspicious financial activity and mitigate financial crime risk. This role will focus on designing, developing, validating, and optimizing advanced analytical models that support transaction monitoring and regulatory compliance initiatives.

The ideal candidate combines strong machine learning and statistical modeling expertise with the ability to translate complex findings into actionable insights for business and risk stakeholders. This individual will work closely with fellow data scientists, risk partners, operational teams, and governance committees to deliver models that are both analytically sound and aligned with regulatory expectations.

This opportunity is well-suited for someone who enjoys solving complex problems, working in highly regulated environments, and influencing strategic decision-making through advanced analytics.

Key Responsibilities
Model Development & Analytics
• Design, develop, test, and deploy machine learning and statistical models that support AML transaction monitoring initiatives.
• Apply advanced analytics techniques to identify suspicious activity patterns, emerging financial crime risks, and opportunities to enhance detection effectiveness.
• Perform feature engineering, model tuning, performance monitoring, and ongoing model optimization.
• Analyze large and complex datasets to uncover trends, anomalies, and actionable insights.
• Support model validation activities and ensure models meet governance and regulatory requirements.

Stakeholder Engagement
• Partner with AML, Risk, Compliance, and operational teams to understand business problems and translate them into analytical solutions.
• Engage with stakeholders to gather requirements, evaluate data availability, and recommend modeling approaches.
• Communicate findings, assumptions, methodologies, and recommendations to both technical and non-technical audiences.
• Present model outcomes and business impacts to leadership teams and governance committees.

Governance & Regulatory Support
• Prepare documentation and supporting materials required for model governance and approval processes.
• Respond to stakeholder, validator, and committee questions regarding model design and performance.
• Ensure adherence to established model development standards, procedures, and regulatory expectations.
• Identify data quality concerns and work with partners to address and remediate issues.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.

Experience
• 4+ years of experience in data science, machine learning, predictive modeling, or advanced analytics.
• Experience developing end-to-end analytical or machine learning models in a professional environment.
• Experience working within a financial institution, banking, or other regulated environment.
• Hands-on experience with model development, implementation, performance monitoring, and ongoing enhancement.
• Exposure to AML, fraud, risk management, compliance, or transaction monitoring environments is highly preferred.

Technical Skills
• Strong proficiency in Python for data analysis, model development, and automation.
• Experience with machine learning algorithms, statistical modeling, and AI techniques.
• Strong understanding of data preparation, feature engineering, and model evaluation methodologies.
• Experience working with large structured and unstructured datasets.
• Familiarity with model governance, validation, and documentation processes.

Education
• Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Economics, or a related quantitative field.

Desired Soft Skills
• Strong collaboration and partnership skills.
• Naturally curious with an investigative and analytical mindset.
• Ability to ask thoughtful questions and challenge assumptions.
• Excellent verbal and written communication skills.
• Strong presentation skills and ability to explain complex concepts to diverse audiences.
• Ability to manage multiple priorities in a fast-paced environment.
• Detail-oriented with a strong focus on quality and process adherence.
• Comfortable navigating governance, regulatory, and committee review processes.

• Experience within AML, Financial Crime, Transaction Monitoring, Fraud Analytics, or Risk Analytics teams.
• Experience using Dataiku for model development and deployment.
• Experience with Neo4j or graph analytics technologies.
• Exposure to network analysis, entity resolution, or relationship modeling.
• Graduate degree (Master's or PhD) in a quantitative discipline.

Benefit packages for this role will start on the 1st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.