Our client, a cutting-edge deep-tech AI platform in the MENA region, is seeking a Senior / Principal Data Scientist This role requires relocation to Riyadh, KSA
As a Machine Learning Scientist, leading initiatives to merge cloud infrastructure, DevOps, and machine learning to automate and deploy advanced computational processes.
This pivotal role is dedicated to developing sophisticated machine-learning models for various industries, significantly advancing our technological evolution.
You will be responsible for
• Lead initiatives to develop and implement strategies for fraud detection and AML
• Collaborate with various teams to define project roadmaps, technical and functional requirements, and deliverables.
• Conduct research, experimentation, and optimization to enhance technical solutions for detecting fraudulent activities.
• Drive the entire life cycle of fraud and AML systems, including the initial concept, implementation, and ongoing maintenance.
• Mentor and guide junior team members and support broader team initiatives, fostering a culture of continuous learning and development.
• Stay updated with industry trends, best practices, and regulatory requirements for fraud detection, AML, and financial crime prevention.
The Must-Haves
• 7+ years of experience in quantitative analytics or data modelling, with strong expertise in machine learning, predictive modelling, and algorithm development.
• 3+ years of experience in building fraud detection ML models or consulting on fraud detection / fraud prevention systems / AML
• Strong experience in Python and SQL.
• Proven experience working with cross-functional and cross-cultural teams.
• Demonstrated leadership capabilities with excellent communication skills and the ability to motivate and inspire a team.
• Strong technical skills to improve, enhance, monitor and review machine learning models
• Advanced degree in a quantitative field such as Computer Science, Statistics, Mathematics,
The Nice-to-Haves :
• Proficient in implementing graph analytics for fraud detection purposes
• Anomaly detection
• Risk scoring at onboarding, event and transaction levels
• Device intelligence applications (fingerprinting, suspicious devices, bot detection)
• Working closely with engineering in implementing ML fraud models and processes
• Working closely with the data science director and product in setting fraud strategy & roadmap.
• Comprehensive knowledge of AWS cloud services and architecture pertinent to data science projects.
Location: Toronto, ON, Canada
Posted: Aug. 27, 2024, 11:41 p.m.
Apply Now Company Website