Fraud Data Scientist Jobs

Data Scientist II - Fraud & Risk

Staff Data Scientist - Fraud & Risk

Data Scientist, KYC Anti Fraud

Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. We are trusted by over 300 million people in 100+ countries for our industry-leading security, user fund transparency, trading engine speed, deep liquidity, and an unmatched portfolio of digital-asset products. Binance offerings range from trading and finance to education, research, payments, institutional services, Web3 features, and more. We leverage the power of digital assets and blockchain to build an inclusive financial ecosystem to advance the freedom of money and improve financial access for people around the world. About the Role We are looking for a Data Scientist to join the Risk Data Science team, focusing on building in-house KYC anti-fraud solutions. The role involves designing and developing AI/ML models to detect identity fraud, with a strong emphasis on ID forgery detection, document recognition, and image-based analysis. You will work closely with Risk, Engineering, Product, and Operations teams to deliver scalable and explainable fraud detection solutions in a fast-paced fintech environment. ### Responsibilities Develop and maintain in-house KYC and anti-fraud solutions, including ID forgery detection, document recognition and verification, and image and video-based fraud analysis. Design, train, fine-tune, and evaluate computer vision and/or LLM-based models for fraud detection, covering image quality assessment, tampering and forgery artefacts, and AI-generated content or deepfake signals. Analyse large-scale, unlabeled or weakly labelled datasets to identify suspicious patterns and generate features for manual review and model training. Collaborate with engineering teams to deploy models into production pipelines, and work closely with Strategy and Operations teams to validate outputs and improve detection coverage. Monitor model performance in production and continuously iterate to improve coverage while maintaining low false-positive rates. ### Requirements Bachelor’s Degree or above in Computer Science, Data Science, AI, or a related field Strong experience in Python and common data science / ML libraries Solid understanding of CV/ML/AI fundamentals Experience with computer vision techniques (e.g. image preprocessing, feature extraction, OCR and etc) Familiarity with model training, fine-tuning, and evaluation Ability to work with large-scale datasets and conduct exploratory data analysis Good problem-solving skills and ability to work independently in a fast-paced environment ### Preferred Experience in KYC, fraud detection, or risk-related domains, with hands-on expertise in ID forgery detection, OCR and document understanding, and image tampering or forgery analysis. Experience applying or fine-tuning LLMs for analysis, classification, or automation tasks, and working with unlabeled or imbalanced datasets. Knowledge of image quality assessment (IQA), frequency-domain analysis, and AI-generated content or deepfake detection techniques. Familiarity with AWS or cloud-based ML workflows, including SageMaker and batch or online inference pipelines. Ability to clearly explain technical results to non-technical stakeholders. Why Binance Shape the future with the world’s leading blockchain ecosystem Collaborate with world-class talent in a user-centric global organization with a flat structure Tackle unique, fast-paced projects with autonomy in an innovative environment Thrive in a results-driven workplace with opportunities for career growth and continuous learning Competitive salary and company benefits Work-from-home arrangement (the arrangement may vary depending on the work nature of the business team) Binance is committed to being an equal opportunity employer. We believe that having a diverse workforce is fundamental to our success.By submitting a job application, you confirm that you have read and agree to our Candidate Privacy Notice.* We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Fraud Data Scientist

As a Fraud Data Scientist at Barclays, you will be responsible for the development and enhancement of fraud detection systems. Applying advanced analytical methods and data-driven approaches, you’ll improve our ability to detect and prevent fraud across a variety of banking products and services. You’ll work closely with other experts in the field, helping us stay one step ahead in addressing fraud risks. To be successful as a Fraud Data Scientist, you should have: A Degree in Mathematics, Statistics, Computer Science, or a related field (or equivalent work experience). Experience in fraud detection, scam prevention, or cybersecurity, ideally in a financial services or banking environment. Proficiency in data analysis, with hands-on experience using tools and languages such as Python, R, SQL and machine learning frameworks. Some other highly valued skills may include: Experience in leading and managing a team of data scientists or similar technical professionals. You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job-specific technical skills. This role will be located at our Northampton office. Purpose of the role To use innovative data analytics and machine learning techniques to extract valuable insights from the bank's data reserves, leveraging these insights to inform strategic decision-making, improve operational efficiency, and drive innovation across the organisation. Accountabilities Identification, collection, extraction of data from various sources, including internal and external sources. Performing data cleaning, wrangling, and transformation to ensure its quality and suitability for analysis. Development and maintenance of efficient data pipelines for automated data acquisition and processing. Design and conduct of statistical and machine learning models to analyse patterns, trends, and relationships in the data. Development and implementation of predictive models to forecast future outcomes and identify potential risks and opportunities. Collaborate with business stakeholders to seek out opportunities to add value from data through Data Science. Assistant Vice President Expectations To advise and influence decision making, contribute to policy development and take responsibility for operational effectiveness. Collaborate closely with other functions/ business divisions. Lead a team performing complex tasks, using well developed professional knowledge and skills to deliver on work that impacts the whole business function. Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives and determination of reward outcomes If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others. OR for an individual contributor, they will lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will identify new directions for assignments and/ or projects, identifying a combination of cross functional methodologies or practices to meet required outcomes. Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues. Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda. Take ownership for managing risk and strengthening controls in relation to the work done. Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function. Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategy. Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practises (in other areas, teams, companies, etc).to solve problems creatively and effectively. Communicate complex information. 'Complex' information could include sensitive information or information that is difficult to communicate because of its content or its audience. Influence or convince stakeholders to achieve outcomes. All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.

Senior Data Scientist, Fraud

Join us in building the future of finance. Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial s