INTL Data Engineer - Financial Crimes Risk

Job Description

Insight Global is partnering with a global leader in digital payments to support their Global Financial Crimes and Customer Protection (GFCCP) organization. This team is at the forefront of combating money laundering, terrorism financing, and financial crimes worldwide through advanced analytics, strong investigative frameworks, and innovative technology.

This is a high-impact opportunity to work on mission-critical initiatives that protect customers and drive smarter, data-backed risk decisions.

Analyze large, complex datasets to define and track KPIs that drive business and risk insights

Build and maintain dashboards and reporting to support decision-making across risk and operations teams

Develop predictive models to forecast risk trends using statistical techniques and machine learning

Design and optimize end-to-end data pipelines and processes to improve automation and efficiency

Partner cross-functionally with leaders and stakeholders to solve risk-related business challenges

Support ad hoc analyses and strategic initiatives tied to fraud, compliance, and risk management

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.

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Strong analytical skillset with hands-on experience in SQL and Excel

Experience working with data visualization tools (Tableau preferred)

Proven ability to translate data into actionable insights

Critical thinking and problem-solving mindset with strong attention to detail

Comfortable working with large datasets and navigating ambiguity

Financial Services Customer Background

Experience with LLMs Experience building machine learning models or predictive analytics solutions

Familiarity with end-to-end data pipeline development

Background in risk, fraud, compliance, or financial services environments

Strong coding mindset (Python, R, or similar tools)

Exposure to working in cross-functional, stakeholder-heavy environments

Recent Financial Services Risk Product Experience