Financial Crime- Data Scientist
Financial Crime- Data Scientist
Are you passionate about using AI and machine learning to make a real-world impact within the world of Financial Crime? Do you thrive on solving complex problems and uncovering hidden patterns in data? Join this forward thinking Fintech, help them protect our customers from financial crimes, starting with APP (Authorised Push Payment) Fraud prevention.
Responsibilities:
- Defining and Evaluating Metrics: Establish and assess key metrics for the AI components of our product, identifying levers for improvement.
- Data Annotation Pipelines: Develop efficient data annotation pipelines utilizing internal assessors and crowdsourcing platforms.
- Machine Learning Implementation: Implement and deploy appropriate Machine Learning algorithms and models.
- Monitoring with BI Tools: Use Business Intelligence tools to monitor key product metrics and the performance of ML models.
Key Tasks:
- Fraud Detection: Access existing systems, evaluate vendor models, and create a roadmap for system improvements aimed at fraud prevention.
- Pattern and Irregularity Analysis: Use statistical tools to uncover patterns and irregularities in data that could indicate fraudulent activities.
- Predictive Modelling: Employ predictive modelling techniques to identify potential fraudulent transactions and behaviours.
- Reporting: Develop concise reports explaining findings, risks, and recommended actions.
- Cross-Department Collaboration: Work closely with other departments to enhance overall security and fraud detection.
Requirements:
- Programming Proficiency: Fluency in Python with deep knowledge of statistical packages and ML/DL libraries/frameworks (e.g., Scikit-learn, NumPy, Keras/TensorFlow/PyTorch) and visualization libraries (e.g., Matplotlib, Plotly, Seaborn).
- Database Skills: Fluency in SQL and familiarity with data visualization tools (e.g., DataStudio, Tableau).
- Statistical Analysis: Basic understanding of statistical analysis.
- Growth Mindset: Proactive and enthusiastic about keeping up-to-date with the latest technologies and researching new ideas.
- Commercial Experience: Experience in implementing production machine learning systems in a commercial environment.
- DevOps Knowledge: Good knowledge of DevOps in a Data Science context (e.g., MLOps) is a plus.
Why Join Us?
- Innovative Environment: Work with cutting-edge technology in a dynamic and innovative environment.
- Impactful Work: Contribute to the safety and security of our customers by preventing financial crimes.
- Professional Growth: Opportunities for continuous learning and professional development.
- Collaborative Culture: Be part of a collaborative team that values your contributions and supports your growth.
If you're ready to make a difference and take on an exciting challenge, we want to hear from you! Apply today to join our team and help us protect our customers from financial crimes.
Reference: 52771035
Please note Reed.co.uk does not communicate with candidates via Whatsapp, and we will never ask you to provide your bank, passport or driving licence details during the application process. To stay safe in your job search and flexible work, we recommend visiting JobsAware, a non-profit, joint industry and law enforcement organisation working to combat labour market abuse. Visit the JobsAware website for information and free expert advice for safer work.
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