AML / Fraud Data Scientist

About Us Solytics Partners is a Global Analytics firm, recognized with multiple industry awards for innovation and excellence. Our team comprises experts with deep domain knowledge in risk, analytics, AI/ML, AML/FCC, and fraud. By converging this expertise with cutting‑edge technologies like AI, Machine Learning, Generative AI, and Large Language Models (LLMs), we deliver powerful automated platforms and incisive point solutions. Our offerings enable clients to streamline and future‑proof their risk, AML, and analytics processes, comply seamlessly with global regulations, and safeguard financial systems. Whether its solving complex challenges or driving operational efficiency, Solytics Partners is committed to empowering organizations with transformative tools to stay ahead in an evolving regulatory landscape. Job Summary We are seeking a highly skilled AML/Fraud Data Scientist with strong expertise in technology particularly in R or Python. The ideal candidate will have 2 to 5 years of experience in data science or analytical roles, and with domain knowledge demonstrating proficiency in detecting and preventing fraudulent activities. Key Responsibilities • Develop and implement models and strategies to identify fraudulent/AML activities and mitigate risks using advanced analytical techniques. • Utilize R, Python, and other analytical tools to analyze large datasets, identifying patterns and trends related to fraud and AML. • Model Development: Create, test, and refine predictive models to forecast potential suspicious activities. • Implement or review systems that monitor and analyze financial transactions, identifying suspicious activities and ensuring compliance with AML regulations. • Conduct thorough risk assessments and develop risk profiles for clients and transactions to determine potential vulnerabilities. • Prepare and submit regulatory reports related to AML and fraud, ensuring accuracy and compliance with relevant laws and regulations. Key Requirements • 2 to 5 years of experience in data science, analytics, or a related role with a focus on AML and fraud detection. • Proficiency in R and Python. • Experience with data analysis tools and techniques. • Familiarity with machine learning algorithms and statistical models. • Strong analytical and problem‑solving skills with the ability to interpret complex data and make data‑driven decisions. • Domain and practical knowledge on Fraud / AML. • Relevant certifications in AML, Fraud Detection, or Data Science. • Knowledge of big data technologies and platforms. • Familiarity with the financial services industry and its regulatory environment.