> Markdown version of [/jobs/ext/1345799-fraud-data-scientist](https://www.wearedevelopers.com/jobs/ext/1345799-fraud-data-scientist). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Fraud Data Scientist. - **Company:** Associated International Brokers Inc. - **Location:** United States (Remote available) - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** A/B Testing, Data Analysis, Data Transformation, Payment Systems, Fraud Prevention and Detection, Graph Database, Python (Programming Language), Machine Learning, Neo4j, SQL Databases, Data Streaming, Feature Engineering, Advanced Reports, Data Management, Databricks - **Published:** July 19, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/p5twb27hrq ## About the Role * 3-5 years' experience working with machine learning-based detection systems including development, validation, deployment, and post-live monitoring. * In-depth knowledge of machine learning algorithms, particularly tree-based models, and anomaly detection performance KPIs. * Hands-on expertise in SQL, Python, and Big Data tools such as Databricks. * Understanding of fraud typologies such as card fraud, payment fraud, account takeover, and mule activity would be desirable. * Exposure to fraud platforms such as Featurespace, TSYS, or similar detection systems is desirable; familiarity with graph database technologies such as Neo4j or TigerGraph is a plus. * Ability to translate data into clear, business-focused insights and work effectively with a wide range of stakeholders. ## Description * Would you like to play a leading role in a team whose ambition is to become a world class fraud function, exceptional at developing talent and turning information into insights? * Do you enjoy collaborating with cross functional teams and influencing business direction with data-backed evidence? * Do you actively seek opportunities for innovation and continuous improvement? What Is The Role We are looking for a technically strong Fraud Data Scientist to join the fraud decisioning capability within AIB. This role will focus on applying data science techniques to fraud detection and prevention in financial transactions, including payments and transfers, while also supporting forward-looking analytical insight across the fraud environment, * Apply domain knowledge in financial fraud to review and enhance existing anomaly detection in payment systems, including business rules and machine learning models. * Support the transformation of new data streams into fraud risk signals to be used by rules and models. * Develop a thorough understanding of the data science lifecycle including data exploration, preprocessing, feature engineering, modelling, validation, and deployment. * Design, build, and maintain predictive models, including decision trees, random forests, and gradient-boosted trees, with a low-level understanding of their algorithms and functioning. * Conduct A/B testing and other validation techniques to ensure the accuracy and reliability of payment rules and models. * Communicate complex data insights to non-technical stakeholders through clear and actionable reporting. * Collaborate with cross-functional teams and support data-driven improvements through exploration, feature engineering, and model enhancement, * Customer First * Ensures Accountability * Collaborates * Eliminates Complexity * Data Analysit * Investigating & Reporting ## Related Videos - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [Detecting Money Laundering with AI](https://www.wearedevelopers.com/videos/111-detecting-money-laundering-with-ai) - [Putting the Graph In GraphQL With The Neo4j GraphQL Library](https://www.wearedevelopers.com/videos/257-putting-the-graph-in-graphql-with-the-neo4j-graphql-library) - [Bringing the power of AI to your application.](https://www.wearedevelopers.com/videos/1010-bringing-the-power-of-ai-to-your-application) - [OLTP in the Lakehouse: Redefining Data for AI Workloads](https://www.wearedevelopers.com/videos/2038-oltp-in-the-lakehouse-redefining-data-for-ai-workloads) - [Cyber Sleuth: Finding Hidden Connections in Cyber Data](https://www.wearedevelopers.com/videos/893-cyber-sleuth-finding-hidden-connections-in-cyber-data) ## Related Articles - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Data Analyst Salary Austria](https://www.wearedevelopers.com/magazine/275-data-analyst-salary-austria) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Analyst Salary in Switzerland](https://www.wearedevelopers.com/magazine/276-data-analyst-salary-in-switzerland)