Zeal Group is an award-winning FinTech organisation offering a variety of products. Founded in 2017, we have grown to a team of 700+ employees across the globe 🌎Our offices and presence are spread across Europe, Asia, North & South Africa, Middle East and South America, with our Technology hubs located in Cyprus and Netherlands 🚀We are a product and people focused company who are passionate about growth, innovative technology, and collaboration 🙌🏼
About the role:
We are seeking a talented and experienced Data Scientist specializing in Trading Anti-Fraud and Client Flow Analysis to join our team. As a Data Scientist in this role, you will be responsible for developing advanced analytical models, algorithms, and techniques to detect and prevent fraudulent activities. Additionally, you will analyse client data and behaviour to identify patterns, insights, and potential risks. The ideal candidate has a strong background in data science, machine learning, and trading fraud detection, with a passion for leveraging data to enhance security and protect against fraudulent activities.
- Develop and implement advanced analytical models and algorithms to detect and prevent fraudulent activities, including trading fraud, account takeovers, identity theft, and other fraudulent behaviours. Utilize machine learning techniques, anomaly detection, and predictive modelling to identify patterns and anomalies indicative of fraudulent activities.
- Analyse client data and behaviour to identify patterns, trends, and potential risks. Utilize statistical analysis and data mining techniques to perform client segmentation, profiling, and risk scoring. Collaborate with cross-functional teams to identify and implement effective fraud prevention strategies.
- Design, build, and implement statistical models and machine learning algorithms for fraud detection and risk assessment. Validate models using appropriate testing methodologies, including back-testing, cross-validation, and performance evaluation.
- Develop visualizations and reports to effectively communicate insights and findings related to fraud detection and client analysis. Present complex concepts and technical findings to both technical and non-technical stakeholders in a clear and concise manner.
- Collaborate with cross-functional teams, including Trading Anti-fraud specialists, cybersecurity experts, and IT professionals, to understand business requirements, define fraud detection rules, and contribute to the development of fraud prevention strategies and methodologies.
- Stay updated with the latest advancements in trading fraud detection techniques, machine learning algorithms, and data analysis methodologies. Explore innovative approaches and technologies to enhance trading fraud prevention capabilities and client analysis.
- Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field. A focus on fraud detection, cybersecurity, or risk management is a plus.
- Significant experience working as a Data Scientist or in a similar role, preferably in the domain of trading anti-fraud or risk management.
- Proficiency in programming languages such as Python or R, with experience in relevant libraries and frameworks (e.g., pandas, scikit-learn, TensorFlow). Strong knowledge of statistical modelling, machine learning, and data mining techniques.
- Experience with data visualization tools (e.g., Tableau, Power BI) is desirable.
- Strong analytical and problem-solving skills with the ability to translate complex business challenges into data-driven solutions.
- Attention to detail and ability to identify patterns and anomalies in large datasets.
- Excellent communication and presentation skills to effectively convey complex concepts to both technical and non-technical stakeholders.
What we can offer you:
- Competitive Salary
- Bonus scheme – Up to 3 months’ salary
- 25 Days annual leave + Public holidays
- Holiday Allowance
- Pension Scheme
- Cycle to work scheme
- 30 Days work from anywhere in the world
- Eye test reimbursement scheme
- Glasses reimbursement scheme
- Gym reimbursement scheme
- Salary Offer 0 ~ $3000
- Experience Level Junior
- Total Years Experience 0-5
- Dropdown field Option 1