Join the FinTech Data Science team to develop ML models for fraud detection and optimize billing systems using AI and NLP techniques.
Available Locations: Lisbon, Portugal or London, United Kingdom
About the Role
We're seeking a Data Scientist to join our FinTech Data Science team. In this role, you will apply advanced statistical analyses and ML models to large datasets to solve challenges in Billing and Fraud. You will lead the development of our foundational fraud detection framework, building the initial ML models to mitigate financial risk. In addition, you will drive innovation in our Billing systems by applying AI to unstructured data to improve user experience. If you are excited to use data to not only optimize our operations but to discover and build the next generation of FinTech products, we would love to hear from you!
The ideal candidate will possess a strong foundational knowledge of data science principles and statistical modeling. Day-to-day responsibilities include:
Required skills, knowledge, and experience:
Bonus Points
About the Role
We're seeking a Data Scientist to join our FinTech Data Science team. In this role, you will apply advanced statistical analyses and ML models to large datasets to solve challenges in Billing and Fraud. You will lead the development of our foundational fraud detection framework, building the initial ML models to mitigate financial risk. In addition, you will drive innovation in our Billing systems by applying AI to unstructured data to improve user experience. If you are excited to use data to not only optimize our operations but to discover and build the next generation of FinTech products, we would love to hear from you!
The ideal candidate will possess a strong foundational knowledge of data science principles and statistical modeling. Day-to-day responsibilities include:
- Collaborate with Product, Engineering, Support and Finance teams to translate complex business requirements into scalable data science solutions for Billing and Fraud
- Lead the design and implementation of foundational Machine Learning models to detect financial anomalies, abuse patterns, and fraud risks
- Leverage AI and NLP techniques to mine unstructured data, such as support logs and user feedback, to identify friction points and uncover hidden improvements in our billing systems
- Manage the full lifecycle of our models, from exploratory analysis and feature engineering to validation, deployment, and monitoring in production
- Proactively identify opportunities to transform data insights into new FinTech product features or strategic business initiatives
- Build and optimize robust data pipelines ensuring data is discoverable and easy to query
Required skills, knowledge, and experience:
- MS/PhD in a quantitative field (CS, Statistics, Math, etc.) with 5+ years of industry experience
- Strong knowledge and hands-on experience in machine learning and statistics
- Experience using LLMs to extract actionable insights from unstructured data
- Proficiency in SQL and Python
- Hands-on experience building and maintaining data pipelines
- Experience deploying machine learning models into production environments
- Ability to navigate ambiguity and lead the development of foundational products from scratch
- Excellent communicator, with a focus on driving impact
Bonus Points
- Experience in FinTech
- Experience working on fraud or support related problems
- Experience building AI agents
Top Skills
AI
Data Pipelines
Machine Learning
Nlp
Python
SQL
Unstructured Data
Cloudflare London, England Office
Riverside Building, 6th Floor, County Hall/The, Belvedere Rd, London, United Kingdom, SE1 7PB
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